What's next in aeronautic connectivity and sensing?

Since the graphene discovery, its applications to electronic and optoelectronic devices have been intensively and thoroughly researched. The extraordinary and unusual electronic and optical properties allow graphene and other two-dimensional (2D) materials to be promising candidates for infrared (IR) and terahertz (THz) photodetectors. Quantity of published papers devoted 2D materials as sensors is huge. However, authors of these papers address them mainly to researches involved in investigations of 2D materials. Up till now, the first test to estimate their place in wide infrared detector family was given in Advances in Optics and Photonics 11(2), 314 379, 2019. In the present paper this topic is treated comprehensively with including both theoretical estimations and many experimental data. In the paper, at the beginning we describe shortly fundamental properties of graphene-based materials and alternative 2D materials, and performance of detectors fabricated with them. Next, the position of 2D material detectors is considered in confrontation with the present stage of infrared and terahertz detectors offered on global market. A new benchmark, so-called "Rule 19", used for prediction of background limited HgCdTe photodiodes operated near room temperature, is introduced. This rule is next treated as the reference for alternative 2D material technologies. The performance comparison concerns the detector responsivty, detectivity and response time. Final conclusions predicts place of 2D material-based detectors in the near future, in wide IR detector family.

This paper deals with the description and evaluation of the M-sequence UWB radar system on chip (SoC). Instead of common 9 th or 12 th order M-sequence generator, the proposed UWB radar includes the 15 th order generator. Therefore, it has significantly longer unambiguous range and is able to exploit the regulatory spectral masks more efficiently. Consequently, it is better suited for sensing applications which require longer range and small dimensions of radar system. The theoretical assumptions are confirmed by experimental measurements in a simple measurement scenario.

The benefits of polarimetric radar technologies are addressed and respective technology gaps are identified for a variety of applications in radar and electronic warfare. Examples of fully polarimetric data processing are provided for FOPEN applications on real data, making use of Polarimetric Whitening Filtering (PWF) with subsequent Polarimetric Matched Filter (PMF) techniques as well as for Polarimetric Space Time Adaptive Processing (Pol-STAP) on simulated data. The performance advantages of these polarimetric approaches are demonstrated and compared with classical processing schemes. Part of these results were elaborated within the framework of the PolRad project, funded by the European Defence Agency (EDA), with the aim to demonstrate the benefits of polarimetric radar technology in defence scenarios for target classification, target detection and tracking of man-made object in vegetated environment as well as for the usability for Electronic Support Measures. Finally in this context a potential outlook is given in terms of technology and timelines for polarimetric applications.

The paper presents results of preliminary field trails of an FMCW (Frequency-Modulated Continuous-Wave) radar intended to use for border protection. A concept of the complete radar system as well as a detailed description of a developed low-cost radar demonstrator based on dual channel analog front end are presented. The field trials results obtained using the demonstrator are presented and discussed carefully in the paper.

The ground based mobile perimeter surveillance of many military and civil infrastructures to detect and track potential threatening targets on ground or in the air is still a very important capability of sensor systems. Such dangerous targets can be suicide attackers or drones, which violate the privacy of individuals or which can be used for spying, smuggling, or acts of terrorism. To demonstrate the possibilities of current technologies and processing methods, a high performance mechanically scanning surveillance radar sensor and a high-resolution camera were successfully combined for these applications. Both sensors have a high measurement update rate of up to 1.6 Hz. The most remarkable feature is the use of a 94 GHz radar sensor with 3D localization, georeferencing, extended Doppler analysis, RCS calibration and multi target tracking for stand-off monitoring in real-time of an area of interest. Furthermore, the real-time images of the multi-sensor system are transferred from the operator's computer to several mobile devices to disseminate an overview of the situation. The implementation of the real-time data processing and the real time data visualization plus the intuitive system control was done successfully. The stored radar and camera data can be used for the conservation of evidence, for further offline processing and for algorithm development.

In cooperation with the German Aerospace Center (DLR) the second Flight Trials of the Sense and Avoid Radar has been completed. The Radar has been tested within a fully capable Sense and Avoid System, which combines Cooperative Sensors such as ADS-B and T-CAS with Non-Cooperative Sensors such as Radar and Electro-Optics. Also the Airborne Weather Radar capability was successfully tested within the flight trials. Both functions work in parallel, which is facilitated by a sophisticated Radar Resource Management. This paper recapitulates the main design drivers of the radar and shows the test results of the Flight Test Trials regarding the Radar functions, which are in particular the Sense and Avoid Radar Function and the Weather Radar Function.

The development of an automotive surface recognition system is an important and yet unsolved task. In the current study we are considering a novel approach to surface classification based on the analysis of the image obtained using the Low Terahertz radar. The proposed experimental technique in combination with a deep convolutional neural network provides high surface classification accuracy.

Automatic Target Recognition (ATR) is one of the strongest growing technology topics, especially in commercial applications like image recognition and automotive. ATR applications in radars established in the fields of defence and protection stayed on a certain level for years, so today there is a strong need to participate in the performance growth enabled by modern technologies. In this paper the ATR potential of the Deep Learning (DL) approach is proved by comparing the performance of a highly mature "classical" concept using feature extraction and several types of classifiers versus several state of the art DL networks and training concepts. The comparison is done on the same large database of Micro Doppler signatures from several classes, as typically used for moving object classification and drone threat assessments. The comparison shows the benefit and potential drawbacks of the different approaches.

Sign language is the primary communication medium for the deaf-mute community. However, the literacy of understanding and using sign language is hard to gain without professional training. In this paper, we explore the use of low power frequency modulated continuous wave radar for automatic sign language recognition. The proposed system is composed of a radar, a sound cluster and a computer for transforming signals to spectrograms. Furthermore, as the time-frequency spectrograms are high-dimensional data with redundant information, we then perform dimensionality reduction by extracting the histogram of oriented gradients features from these spectrograms. The features are finally classified by the k-Nearest Neighbour algorithm and a classification result of 95.8% is achieved on the five testing signs. The impact of the k value in the k-Nearest Neighbour is also investigated.

In this paper an efficient wideband Direction of Arrival (DoA) and frequency estimation technique is presented which uses only a single snapshot from a multi-beam antenna array. The simultaneous spatial beams (beamspace) are generated by a Rotman lens which consists of a free-space true time delay network attached to a Uniform Linear Array (ULA) of broadband Vivaldi antenna elements. The proposed technique uses machine learning techniques to establish an optimal Neural Network (NN) configuration obtained with a training set. To improve the spatial and frequency space resolution a further estimation stage follows to the NN topology. This results in a lower computational load during the training phase and finally a very fast estimation of direction and frequency of the impinging signal. The performance is evaluated by measurements obtained in an anechoic chamber.

To prevent interference to other radio systems, the measurement and verification of unwanted emission levels, in the spurious domain and the out-of-band domain, are required for the radar systems. Since there is only one commercially available measurement site in the world capable of measuring unwanted emissions in the spurious domain and the out-of-band domain of a marine radar, more measurement sites are necessary. We are going to design and construct a measurement site in Japan. In this paper, we introduce the measurement site and propose how to control multipath propagation. There are three techniques to control multipath waves: narrow antenna beam width, diffuse reflection on the grassy ground, and the use of a reflected wave barrier. A method for estimating the reflection point is also proposed. It uses the interference fringes of the direct wave and reflection waves. The site insertion loss measurements are within +/- 4 dB of the theoretical site insertion loss of free-space.

Multi-beam antenna systems are the basic technology that is used in developed fifth-generation systems. This article is devoted to assessing the impact of a multi-beam antenna system on the interference level in the downlink. These interference are generated by neighboring base station antenna beams. The presented analysis is based on simulation studies in which the multi-elliptic propagation model is used. Transmission characteristics of propagation environments such as power delay profile and antenna beam patterns that define the geometric structure of the model were adopted on the basis of the 3GPP standard. The obtained results show the possibility of using the presented method to assess the separation angle between co-channel beams. It is the basis for minimizing spectral resources in the system.

Antenna arrays are used in many applications, such as space technology or long distance communications. However, there is often an issue of large antennas' sizes for such systems. For example, such a problem is urgent in wideband arrays. This is important because then the distance between antennas in the equidistant arrays cannot be hold. Thus the side diffraction maximums appear. Here we show that conversion to non-equidistant antenna arrays decreases radiation pattern's side lobes for direct radiation and deflection. Based on the methods in the manuscript, we reduced side lobes of our array to -10dB compared to the main lobe. These methods allow calculating non-equidistant antenna arrays with high accuracy using information about antenna's characteristics. Thus, the side radiation is decreased and the antenna array efficiency is improved.

Contemporary UWB positioning systems are able to provide excellent positioning accuracy. However, if the system is deployed in an environment where the propagation channel is demanding the positioning errors are significantly bigger. The paper contains a description of a method for correction of time difference of arrival measurement results. The applied offset corresponding to current tag location. Fingerprinting technique is used for correction data preparation and selection. The method efficiency was verified with measurements performed with UWB positioning system. The paper contains description of the proposed method. Results of experiments are included and discussed in the paper.

In this paper, the concept of direction of arrival (DoA) estimation using electronically steerable parasitic array radiator (ESPAR) antenna designed to operate in IEEE 802.11p vehicular communication standard has been investigated with respect to different possible elevation angles of a radio frequency (RF) signal impinging the antenna. To this end, two different possible sets of the 3D antenna radiation patterns have been used together with power-pattern cross-correlation (PPCC) algorithm and its extension that covers multiple calibration planes (PPCCMCP). Numerical simulations of the PPCC and PPCC-MCP angle estimation procedures at 5.89 GHz have been performed to verify the overall DoA estimation accuracies in the horizontal plane for different, and unknown at the moment of estimation, elevation angles.

In this paper, a 1x2 dual-band microstrip antenna array configuration in FOWLP technology for 5G applications operating in the 28 GHz and 38 GHz frequency bands is proposed. For the first time the antenna array is designed, simulated and fabricated on 200 µm mold substrate material for a compact 1 cmx1 cm Antenna-in-Package module. Results show a good correlation between simulation and measurement. A measured impedance bandwidth of 400 MHz is achieved at both 28 GHz and 38 GHz frequency bands, whereas the maximum antenna gain is approximately 6 dBi.

Sparse decomposition and l0 norm minimization approach to Synthetic Aperture Radar (SAR) image reconstruction is discussed. A linear frequency modulation (LFM) complex signal reflected from the earth surface, is decomposed by two-dimensional (2-D) multiplication of three matrices - azimuth Discrete Fourier Transform (DFT) matrix, image matrix and range DFT matrix. Image reconstruction procedure based on l0 norm minimization is applied to reduced number of measurements defined by randomly generated azimuth and range sensing matrix. The geometry of the scene is described by a two-dimensional surface function. The sparsity of the surface is achieved by multiplication of the surface function with a random binary matrix. Results of numerical experiments are provided to illustrate the suggested approach and to prove the correctness of the algorithm.

Inverse Synthetic Aperture Radar (ISAR) exploits the motion of the target to achieve cross range imaging, as opposed to its range resolving capability (along line of sight) which relies on the bandwidth of the signal. In ISAR imaging, it is usually the case that the relative motion between the radar and the target of interest is unknown. The lack of precise knowledge of this relative motion affects the quality of the reconstructed image. Therefore, estimating the relative motion is an essential step for ISAR imaging. Compared to the two dimensional ISAR, the three dimensional ISAR imaging requires more motion components to be estimated. In this paper we present a sparsity driven algorithm that tackles the problem of three dimensional ISAR auto-focusing based on relative motion estimation.

In order to avoid the receiver saturation, the low-earth-orbit spaceborne MiniSAR system uses the integrated transceiver for data collection. However, this kind of transceiver can be in one state of transmitting or receiving only at any one time, which will cause the periodic loss of collected data. In this paper, an L2,1-norm regularization based sparse SAR imaging method is proposed to process the azimuth periodic block sampling data. Because the ghosting terms caused by the periodic block sampling are considered in the scene recovery, it can effectively suppress the ghosts to achieve high-resolution sparse scene reconstruction.

Maximum unambiguous range in pulsed radars is a function of transmit inter pulse period(T). For high speed and highly maneuvering targets the inter pulse period has to be sufficiently small to extract intelligible information from radar returns for quick threat analysis and possible target engagement. So a high pulse repetition frequency (HPRF) system is required to work with this class of targets. But HPRF systems have ambiguous range problem which requires complex processing schemes for range extraction. And to utilize the unambiguous range rate information for range extraction we require initial position of the target, which mandates additional communication link with other sensors in the network. On the other hand, low PRF (LPRF) systems have unambiguous range information but very high inter pulse period which is detrimental for tracking high speed targets. In this paper we propose interleaved low PRF processing amidst staggered high PRFs to leverage the benefits of both the schemes. We propose fusion of range unfolding algorithm for staggered high PRFs based on Optimized Chinese Remainder Theorem(OCRT) along with compressed sensing(CS) based interleaved low PRF processing for initial range estimation and to provide range reference for correcting estimation errors at periodic intervals. Both the methods run in parallel channels and the output is fused to obtain improved range estimates.

In this paper we extend the successive concave sparsity approximation (SCSA) algorithm to complex numbers in order to make it available for applications benefiting of it e.g. radar applications. SCSA is an attractive reconstruction algorithm for compressive sensing (CS) problems due to its high reconstruction performance (superior to l1 algorithms) and in particular since it does not require any "hard" parameters,unlike all hard thresholding (HT) algorithms, which may be unknown in radar applications. We call this extended version complex successive concave sparsity approximation (CSCSA) and evaluate its performance by use of phase transition plots for random and discrete Fourier transform (DFT) sensing operators and further compare it with the two well known algorithms normalized iterative hard thresholding (NIHT) and fast iterative shrinkage-thresholding algorithm (FISTA), where we especially show how the reconstruction performance of NIHT declines in case of wrongly assumed parameters.

The capability of passive radar employing radio telescope as a receiver and digital radio broadcasting (DAB+) as an illuminator of opportunity is analyzed in the paper. The principle of LOFAR radio telescope is presented with deep analyses of using such radio telescope as passive radar for detection of aerial (airplanes) and space (satellite) targets. The theoretical considerations are illustrated by the description of signal processing schema and presentation of measurement results.

In this paper practical results of drone detection and tracking in a DVB-T2 passive radar system are presented. DVB-T2 signal from TV tower was used to detect and measure distance and velocity of a drone. To increase SNR, adaptive filtering and re-modulation of DVB-T2 signal was applied before the detection. Since integration time of the reflected signal is large, a non-trivial fast convolution algorithm was used to reduce the computational expense. Detection was done by CFAR algorithm. Finally, it was shown that in range-doppler matrix peaks from drone's propellers are visible what can be used for its type identification

This paper shows a study about the use of sparse frequency signals for the improvement of passive radar systems capabilities based on DVB-T. The analysis was performed on real signals acquired by IDEPAR, a demonstrator developed at the University of Alcalá. Data has been obtained by upgrading platforms acquisition cards to USRP X310, which have enough bandwidth to acquire groups of DVB-T channels scattered in frequency. A double analysis has been carried out/performed to determine the improvement of detector capacity by comparing the initial version of IDEPAR and the updated one. Firstly, the pedestal estimation of the ambiguity function of the acquired reference signal is presented, which is directly related to the signal-to-noise ratio of the system. Secondly, the Range-Doppler maps obtained after the coherent processing of the signals are analyzed. In this case, the average signal to interference ratio along the trajectory of three targets is calculated. The results show an improvement in capabilities by increasing the useful bandwidth of the acquired signals.

Device-Free Passive Localization (DFPL) is capable of detecting and locating an object without requiring the object to hold any device, nor to participate actively in the localization process. This system is based on wireless sensor networks (WSN) and analyzes the reflections of wireless signals from the object. A method to localize an object based on time-delays in the channel impulse response (CIR) and an elliptical model is presented. Radar imaging is used to generate a heatmap of the environment. With the help of IEEE 802.15.4 ranging modules the algorithm is evaluated with measurements in a radio-frequency anechoic chamber.

The purpose of this work was to create a wireless Internet-of-Things (IoT) communication module for a device for measuring soil parameters in a field environment. The module uses the Low Power Wide Area Network (LPWAN) technology to exchange data with an external database. This paper contains information about design assumptions, research on the existing long-range communication technology solutions and description of the design process.

This paper presents a method for determining a six-port reflectometer's response to a matched load with the use of partially known calibration loads. It utilizes nine calibration loads which can be of unknown magnitude and phase, however, three of them must exhibit magnitudes possibly close to each other with a reasonable phase separation. The algorithm was tested with the use of an exemplary broadband six-port reflectometer operating over the frequency range from 2.5 GHz to 3.5 GHz. The power values obtained using the proposed method are very close to those directly measured by the six-port reflectometer with a broadband matched load from precision calibration kit connected as DUT.

In this paper authors presents very important problem of estimation capacitance structures used in MEMS sensors. The importance comes from fact that during operation, inertial sensors which are build of solid materials deform because of external forces acting on them. Therefore typical capacitor consists of some electrodes changes its value because electrode changes its orientation. Here authors use analytical and FEM results to compare capacitance results and impact on accuracy of measurement.

In the paper authors take into considerations results of analysis both MEMS accelerometers and gyroscopes under performance that can be changed by some geometry details modifications. Authors considers different types of shapes of springs to show, how they influence on total device operations.

The instantaneous frequency measurement (IFM) devices are very useful for very fast measurement of current frequency value of microwave signals even if their duration is extremely short. A fast measurement of temporary value of frequency is based on evaluation of a phase difference of signals propagating through the microwave transmission lines having unequal but known lengths. This phase difference is provided by so-called proportional phase shift forming network (PPhSFN), and the phase difference measurement is performed by the microwave phase discriminator (MPhD). The main segment of MPhD is a microwave six-port made of several microwave splitters and combiners. The paper presents integrated version of microwave correlator containing PPhFS and six-port on a single printed circuit board (PCB). The developed device was designed to work over WiFi frequency range. The frequency bandwidth of the made correlator reaches nearly one octave.

The paper presents the attempt of finding optimal solutions regarding the emission type, basic emission parameters and channel capacity for the trans-ice longwave communication channel, as deployed in June 2019 during the first edition of the IGLUNA programme - a simulated lunar habitat in the Klein Matterhorn glacier in Switzerland. The experimental system is compared to lowland high-power longwave systems, the optimal emission type for different conditions (modulation index, demanded presence of carrier) is presented and the maximum possible channel capacity in relation to the achieved signal readability is calculated.

High power electromagnetic pulse weapon (EMP) is a new kind of weapon which can directly transmit high power microwave to damage the target electronic equipment. This paper introduces the damage mechanism of high power microwave, describes the working principle of the marine navigation radar and the front-end structure of receiver. The damage ability of high power microwave to marine navigation radar receiver is calculated and analyzed, at the same time, the damage range of high power microwave to marine navigation radar is given under the different states of power center and power edge.

3D printing offers a very innovative opportunity for creating cheap or special rf-components like waveguides, couplers or antennas. However, these components require electrical conductive materials to be built of. Therefore, selective laser melting of metal powder is also an attractive production technology. In this paper, horn antennas and a directional coupler at 24 GHz are shown and their production technologies are compared. By presenting a K-band branchline coupler it is shown that selective laser melting has some advantages over 3D printing.

The proposed radar system is characterized by cheap equipment (omnidirectional microphones, a computer for signal processing, and peripherals) and by the special algorithm of signal processing, which has been developed and tested during full-scale experiments with real targets: aircrafts and UAVs. A key feature of the developed algorithm is a fast method of estimation of wideband ambiguity function. In addition, the algorithm provides visualization of the target location process using the projection of the ambiguity function onto a coordinate plane. The developed radar system is proposed to use for aircraft noise management in the vicinity of an airport and for localization of small-sized flying vehicles. The results of the experiments are presented in the paper

the Weightless(-P) is a narrowband communication system designed for the Internet of Things, along with some other counterparts such as Lora and SigFox. As a system dedicated specifically for long-range operations, it possesses a considerable processing gain for the energetic link budget improvement and a remarkable immunity to multipath and interference. The paper describes outcomes of measurement campaign during which the Weightless(-P) performance was tested against variable interference, generated in an anechoic chamber. Results allow to quantitatively appraise the system behavior under these harsh conditions with respect to the modulation and the resultant bandwidth. The outcomes allowed to propose recommendations regarding the use of particular system settings to optimally fit environmental conditions. Finally, the paper provides an analysis in which CNIR is converted to the Interference Margin and its value is checked against an intentional jammer approaching the base station to verify how different Weightless operational modes respond to electromagnetic jamming.

This paper deals with a model-order reduction method, applied to speed-up the simulations of MIMO antenna arrays, performed by means of finite element method. The obtained results of the numerical tests show that the described technique is reliable and considerably increases the efficiency of the standard finite element method.

Radar technology in the mm-wave frequency band is a promising approach for the detection of birds and bats at wind turbine installations in order to reduce fatalities either by direct collision of the animals with the rotor blades or through barotrauma. In this paper we present an FMCW radar system with 1 Tx and 9 Rx operating in the Ka-band from 33.4 GHz to 36.0 GHz. The radar system is installed at the tower of a 2MW wind energy plant about 95m above ground. The data acquisition is described in this paper including the real-time processing pipeline, followed by exemplary bird detections. Also the detection of drones, serving here as an artificial flying object with a defined flight path, will be presented and discussed. Validation is performed by concurrent camera recordings.

The specially calculated reflecting surfaces with Stealth invisible quality designed for to avoid vertical ones for ra-dar beam and to reflect beam "to the milk". Stealth coatings with the full absorption of the micro-wave radar radiation on his surfaces are blackbody and reasonable to consider it as the matched loading with the corresponding physical outside temperature. A lot of news and minding has place about the Stealth application especially in the contest of an airplanes. Possi-bility to avoid the disclosing of an airplane on the big dis-tances is main advantage of this Stealth "addition" against of the radars. But in much cases for the microwave radi-ometers this Stealth coating can be good for the real deter-mination by the passive devices because their job based on the measuring the radio-brightness contrast between Stealth objects and the background of the environment/s (sky is cold, Earth is warm). The aim of this short report - to present some under-standing about to use radiometer about Stealth objects

In this paper, influence of dielectric overlay permittivity on miniaturized ESPAR antenna parameters is presented. ESPAR antenna is a low-cost and energy-efficient way to implement beam steering capability to a node and improve network performance. The antenna size reduction is obtained by embedding its active and passive elements in ABS based materials of relative permittivity equal to 4, 5.5 and 7.5 in order to achieve network node compact size. Simulation results of three optimized for particular dielectric constant designs are presented and tradeoff between dimensions reduction and performance is discussed. Selected materials and antenna design are dedicated to be fabricated in 3D print technology, so can be easily prototyped.

Microwave propagation in the atmosphere is affected by air temperature, humidity, attitude, and other factors, there are many related researches on the above influencing factors, but relatively few researches are attached on the microwave propagation characteristics under the condition of sea salt mist. It is of great significance to clarify the law of microwave propagation attenuation under the condition of salt mist for the microwave applications such as maritime communication and radar detection. Firstly, the parameters of the salt mist environment are analyzed and modeled in this paper, and it is driven that the relationship between the concentration of the salt mist and the dielectric constant of the atmosphere. Then, based on the FDTD numerical analysis, the microwave propagation law under different concentration of the salt mist is calculated and compared with the theoretical analysis results.

This paper describes an experimental setup that was built to imitate the performance of the new microwave personnel screening system, in which synthetic aperture is formed due to relative motion of the subject in the vicinity of a sparse antenna array. The RGB-D sensor captures a color image and a depth map of a still scene with a mannequin, while the compact network analyzer, which is moved by a two-dimensional scanner, acquires the samples of the radar signal reflected from the same scene. The mannequin is moved by the third linear drive module to another position, creating the next still scene to be scanned and captured similarly during a single experiment. The collected data is stored for the following joint processing. Preliminary radar images of concealed objects on mannequin are obtained and demonstrated. The use cases of the experimental setup are described toward designing a sparse electronically switched antenna array: finding the required number of the channels, choosing proper frequency band and bandwidth, antenna type, and others.

The paper presents an algorithm for positioning of a handheld ground-penetrating radar antenna. The algorithm has been elaborated for processing range measurements in a currently developed positioning system based on ultrawideband radio modules. Such a system is planned to be used as a support for a handheld ground-penetrating radar as continuous and accurate positioning of its antenna can facilitate creation of high-quality subsurface images. The paper contains a short description of the developed system and focuses on its Kalman filter used for positioning. Here, we consider using a novel dynamics model, based on a pendulum motion model, which provides a more adequate description of the antenna's dynamics than abstract position-velocity or position-velocity-acceleration models, commonly used in navigation systems. Chosen simulation results which support this claim are presented.

The paper presents an implementation of analog front-end designed for use in an X-band Frequency Modulated Continuous Wave (FMCW) radar system. Fine range resolution is achieved because of using more than 1 GHz of bandwidth, which is achieved through application of frequency multipliers. The system has been tested in laboratory as well as in a real environment using a USRP (Universal Software Radio Peripheral) device for both, waveform generation and beat signal digitization.

Background subtraction is usual step in impulse radar applications. It is used to not only remove clutter - reflections of all the stationary, mostly irrelevant objects, but also crosstalk. Various techniques are used for clutter/crosstalk removal. These are briefly over-viewed. Focus of this paper, however, is on proposed method of adaptive background subtraction, which is statistical real time method based on developments of entirely different field (Computer Vision)

This paper explores the possibility of using a synthetic aperture radar to detect surface defects of rails and measure parameters of rail junctions. Experimental data were obtained with a setup consisting of a two-coordinate electromechanical scanner and a radar emitting continuous stepped-frequency signal in the range of 22.2 - 26.2 GHz. As an object of study, fragments of narrow-gauge rails were used, in which surface defects of various sizes and depths were created. A phase method for radar signal processing based on the backward propagation of its wavefront was developed, with which radar images of rails with defects were obtained. Experimental studies have shown that the developed rail surface imaging method allows detecting the presence and measuring characteristics of cracks on the tread, cleavages of the railhead, the width of the joint gap and the magnitude of the vertical step at the rails joint. High accuracy and sensitivity of the radar method, confirmed with the contact measurements matching, allow using it for fast noncontact diagnostics of the rails condition.

For polarimetric synthetic aperture radar (PolSAR) images, building extraction has been a challenging topic for long time in applications of land-use and land-cover analysis. Due to similar structures of buildings and such vegetation as forest, they often exhibit similar PolSAR scattering characteristics that are often difficult to distinguishing. Recently, deep Convolutional Neural Network (CNN) has been widely investigated for image processing with many promising results. This paper proposes a method that combines polarimetric features with the CNN network to realize the comprehensive utilization of polarimetric and contextual information of PolSAR data for the extraction of building areas in PolSAR images. Comparison experiments on both ESAR and EMISAR L-band PolSAR datasets show that the proposed method can generate better results for building extraction.

Recently, Interest on circular SAR (CSAR) has been increased in researchers. The sub-aperture division and trajectory reconstruction of ground moving target are important parts of the CSAR research. Firstly, the CSAR sub-aperture is fitted by a second-order curve, which achieves better focusing quality than the traditional fitting method. Next, parameter estimation accuracy is improved of each CSAR sub-aperture. Finally, the trajectory of ground moving target is reconstructed. Simulated data are used to prove the effectiveness and correctness of the proposed method.

This paper introduce an approach for detecting bridges when the difference in radar echo energy is not obvious. It consists of two steps: extracting targets with high anisotropy and detecting bridge. Firstly, by image segmentation based on the feature of multi-aperture polarimetric entropy, we get targets with high certainty. And then we utilize edge detection to extract straight line segmentations. Finally, the parallel straight line segmentations which meet the bridges' geometric properties are selected as bridges. The proposed approach has been test with polarimetric CSAR data, and the experimental results show that our method can detect bridges effectively.

A novel global range alignment technique for inverse synthetic aperture radar (ISAR) imaging is presented in this paper. Instead of requiring the parametric model for the relative offset amongst the range profiles, the alignment is investigated from the viewpoint of optimization, where the minimization of the entropy of the sum range profile (SRP) is employed as the optimization criterion. The precise range alignment within a range cell can be achieved by implementing the proposed algorithm. With respect to the existing global method, the proposed one does not require any interpolation operation and multidimensional search operation. Experimental results based on real measured data of maritime non-cooperative target validate the effectiveness and the efficiency of the proposed algorithm.

In this paper, a general iterative thresholding algorithm (ITA) for solving Lq-norm regularization problem is proposed to achieve the synthetic aperture radar (SAR) image feature enhancement. Compared with the reconstructed images by matched filtering (MF) based method, the proposed method recovered images have lower sidelobes, reduced noise and clutter, which improves the image quality effectively. Experiments basedon Gaofen-3 (GF-3) SAR complex image data are used to validate the proposed method.

A real-time imaging right side-looking synthetic aperture radar (SAR) motion error model is established in this paper, and a center beam motion compensation algorithm based on inertial navigation and phase gradient autofocus (PGA) motion error estimation is adopted. The algorithm compensates the echo envelope and phase separately, and uses the inertial navigation data to straighten the echo envelope with motion error, and then uses the phase gradient autofocus algorithm to estimate and compensate the phase error of the echo. In view of the characteristics of real-time imaging, such as short time, large amount of computation and limited computing resources, the algorithm cancels the steps of range migration correction, projects the motion error vector on the slant plane, and completes envelope correction and phase error estimation. The method has a small amount of calculation and can meet the resolution requirement. The simulation results show that it can obtain high quality SAR images.

Surveillance radars form the first line of defense in border areas. But due to highly uneven terrains, there are pockets of vulnerability for the enemy to move undetected till they are in the blind range of the radar. This class of targets are termed the 'pop up' targets. They pose a serious threat as they can inflict severe damage to life and property. Blind ranges occur by way of design in pulsed radars. To minimize the blind range problem, multistatic radar configuration or dual pulse trans- mission methods were proposed. Multistatic radar configuration is highly hardware intensive and dual pulse transmission could only reduce the blind range, not eliminate it. In this work we propose, elimination of blind range using deep learning based video tracking for mono static surveillance radars. Since radars operate in deploy and forget mode, visual system must also operate in a similar way for added advantage. Deep Learning paved way for automatic target detection and classification. However, a deep learning architecture is inherently not capable of tracking because of frame to frame independence in processing. To overcome this limitation, we use prior information from past detections to establish frame to frame correlation and predict future positions of target using a method inspired from CFAR in a parallel channel for target tracking.

Space-Time Adaptive Processing (STAP) enables detection of a moving object against the background of strong interference by radar. The fundamental principles of the STAP technique for radar signal processing in particular, detecting slow moving objects against interference. are presented in this paper. The parameter (improvement factor), determining the performance of any linear processor was analysed. A disturbance model has been proposed, for which the dependence determining the performance of any STAP processor has been derived. The results of simulation of the optimal processor performance against the suboptimal processor for three different values of noise to interference ratios in reference channels were presented in the paper.

This paper concerns the problem of maximum likelihood (ML) estimation in the case of impulsive observations modeled by heavy-tailed α-stable distributions. To describe analytically the cost function in ML estimation criterion the Fox function representation of α-stable distributions is used.

The paper presents the results of experimental studies on evaluation of employing digital predistortion based on simple feedforward neural network for linearization of microwave power amplifiers. The influence of the number of neurons in the hidden layer, the number of delayed input samples at the input of neural network, as well as the number of samples taken for learning a neural network were studied and discussed in the paper. The main goal of this work was to establish the minimal configuration of the neural network which can be used for linearization of power amplifiers excited by wideband and high PAPR signals, e.g. LTE. The results obtained for neural networks were compared with the results obtained for the conventional predistortion method based on memory polynomial.

Target initiation is one of the most complex parts of the Multi-Static Primary Surveillance Radar (MSPSR) tracking system. Many approaches to solving this problem exist and they mainly focus on decreasing the computational complexity by reducing the number of bistatic tracks in each hypothesis. Another approaches using target movement model assumption or extended set of measurements such as Angle of Arrival (AoA) were also proposed. However, such information may not be available in every system. In this paper, we propose target initiation/deghosting algorithm based on Expectation Maximization (EM) algorithm which focuses on likelihood maximization over the whole set of bistatic measurements. The algorithm description is presented with the detailed analysis of available options for each step. We also discuss advantages of our approach and present some results using simulated data.

Commercial ADS-B data providers deliver massive amounts of continuous data for aircraft traffic worldwide. They are therefore an ideal source for statistical analysis of traffic flows and anomaly detection. By clearly identifying the aircraft using the ICAO code, unique trajectories are obtained worldwide that allow the pattern-of-life of each aircraft to be understood. Furthermore, with modern machine learning technologies and parallel processing frameworks such as Spark, heat maps can be generated and areas of interest, e.g. airports, can be found, which in turn are a starting point for further analysis. The investigation of the change over time of these statistics is part of this paper, as well as the detection of anomalies in the statistics with the usage of an autoencoder deep learning network.

In this paper, a linear least squares (LLS) estimator to solve the range-based positioning problem is investigated. We show that the LLS estimation can use a subset of or the whole available information. The former yields many single set (SS) solutions and the later yields the full set (FS) solution. We also show that the FS solution can refine the SS solutions. An experiment with phase of arrival (PoA) measurements demonstrates that the FS and SS solutions have different accuracies. The FS solution corresponds to the average of the SS solutions. The FS solution was utilized to reduce the SS positioning errors by about 8-28%.

Random Finite Sets become a prominent method for the definition of Bayesian multi target tracking. Often these tracking methods are derived by probability generating functional which requires a broader mathematical background. This paper considers a concrete implementation of a rather advanced type of Bayesian Multi Target Tracking - the so-called Gaussian Poisson Multi Bernoulli Mixture Filter. The aim is to introduce this tracking technique, its implementation, specifics and possible applications.

Modern surveillance networks are able to provide trajectories of all kinds of vessels and aircraft worldwide or at least within extended environments. Best known are Automatic Dependent Surveillance - Broadcast (ADS-B) and (Satellite-) Automatic Identification System (AIS) used in air and maritime surveillance. Both of them are cooperative systems. Besides these systems, sensor networks based on ground installations or mounted on airborne and space-based platforms deliver object trajectories independent of any cooperation. Examples include GMTI radar-based systems operating on UAV platforms or imaging systems based on high altitude pseudo satellites (HAPS) and satellites. These surveillance systems enable the extraction of mid- and long-term trajectories of any kind of objects. The real challenge will be to place the trajectories into the right context and to generate situational awareness and estimate the intents of the tracked objects. Activity-based intelligence and the determination of patterns of life are a significant challenge for new systems. In this paper we present use cases addressing i) clustering techniques to identify areas of interest and patterns of life, ii) supervised machine learning for ship type and activity classification, and iii) the generation of spatio-temporal thematic heat-maps to assist routing and mission planning. Finally, these new data analytic techniques have to be integrated in existing near real time surveillance systems. This requires specific system architectures as well as a completely new software and hardware landscape. In summary, trajectory-based data analytics, machine learning and risk assessment is embedded on local or global clouds and uses dedicated mechanisms for distributed and parallel processing.

The article analyses the possibility for surveillance airplanes by using solar radio emission in a forward scatter radar system. It's estimated as the magnitude of SNR at the input of the signal detector calculated depending on the size of airplanes, the way of the airplanes moving relative to the baseline (perpendicularly or parallel) for various values of the solar radio emission. The time of the contact of airplanes with the receiver beam influences on the duration of the signal received from airplanes. Changes in the angular width of the FS zone and in values of the aircraft FS RCS depending on the frequency values of the solar radio emission are also taken account in the calculation of SNR.

Recently proposed methods for generation of entangled (quantum correlated) signals directly in microwave frequency range give more chances for design of QR for long- range applications. In such applications, the range resolution capability is of a great importance. Using analogy of signal generation and processing in Noise Radar and Quantum Radar we describe a novel concept for Stepped-Frequency QR (SF- QR) design which enables preserving quantum properties of probing signals and provide range resolution capability in SF- QR.

Ground Noise SAR exploits either special antenna with pattern synthesis or Tx/Rx antenna motion along a rail path. In both cases, the azimuth resolution is limited by the available/achievable length of Tx/Rx physical antenna motion. However, in many applications it may be not sufficient to provide the required azimuth resolution. At the same time, a sub-meter range resolution is readily achievable with nowadays fast ADCs and wideband sources of random signals. We consider a special operational mode for enhancement of the azimuth resolution via implementing of alternation of SAR and interferometric modes to enhance azimuth resolution (when a target was detected with a high range resolution) via coherent processing of the data obtained from different Rx units of bistatic Ground Noise SAR

Waveform design and optimization algorithms generally assume a zero-Doppler ideal case to reach an optimum or satisfactory solution in terms of the matched filter output. Therefore, its performance is usually characterized only in terms of the resultant waveforms autocorrelation function, neglecting the practical situation in which the received signal is modulated by the target's Doppler shift. Within this context, this work investigates the Doppler mismatch effects in the Integrated Sidelobe Level (ISL) performance of previously designed/optimized noise waveforms. The analysis has shown that, despite much better results for steady targets, the increasing Doppler mismatch reduces the ISL performance of optimized waveforms, until similar levels achieved when no optimization is performed. To address that, a subpulse Doppler processing approach is also considered, and the results have shown that, besides increasing the Doppler tolerance, it has also increased the optimized waveform robustness to the Doppler mismatch, reducing the resultant ISL loss and thus extending its applicability.

Given the nature of current evolving threats, border security has become of paramount importance both in civilian and military application. In particular, both air and maritime borders are threatened by unlawful activities which employ new technologies and require the use of more effective surveillance sensors. Beside facing both civilian and military issues, allowing for all weather/all day operations, new solutions for border security must deal with the fact that smugglers and illegal dealers might be able to detect and deceive surveillance systems. For this reason, the new solution proposed within the NORMA project consists of a network of noise radar with covert and LPI (Low Probability of intercept) surveillance capabilities. The capability of the radar to be operative all weather all days 24 hour per day accomplished with the main characteristic of transmitting noise-like wideband waveforms with imaging capability is a powerful solution to have an LPI land and sea border surveillance also in critical and The main objective of the NORMA project is to implement an innovative solution that addresses the user needs for covert surveillance. In such a scenario, a noise radar network offers the potential for LPI (Low Probability of Intercept) monitoring whilst guaranteeing the imaging and tracking capabilities.

This paper experimentally proves the ability of millimeter wave radar to provide visibility of objects in a fire. The operation of an imaging radar at a frequency of 79 GHz was investigated under various real conditions, including fire with strong flame, dense smoke, and water vapor. Absorption of the radar signal was measured and the results are in accordance with theoretical calculations. The analysis of the experimental results allows us to conclude that there are good prospects for millimeter wave radar in the field of firefighting equipment for vision and navigation.

In this paper we present the statistical analysis of bistatic rural ground clutter for different terrain types. Compared to state-of-the-art analysis we present clutter models for subdivisions of rural environments. Therefore, four measurement campaigns have been carried out during summer of 2019 in four different rural terrain types, namely a field with low vegetation, with high vegetation, plantation of small trees and forest environment representing a typical rural German environment. The measurements have been carried out in the radar relevant X-Band at a center frequency of 8.85 GHz and with a bandwidth of 100 MHz. The distinction of the rural terrain into different types enables a more precise and accurate clutter analysis and modelling of the statistical properties as shown in the presented results. The statistical properties are derived from the calculated probability density functions and the corresponding cumulative density functions for each of the four terrain types from the measured range-Doppler domain data.

In this work we propose a method of clutter deconvolution and modeling using experimentally obtained UWB radar data. The obtained clutter models are then used for random sequence encoding (RSE) of radar-communication (radarcom) signals to achieve clutter-masked transmissions and improve covertness of the scheme. We present the results of clutter modeling from the laboratory data obtained with the software-defined OFDM radar system. We also present the results of communication and radar performance of the radarcom signals created using the derived clutter model. It is shown that this method has the potential to achieve secure communications in adversarial conditions, while simultaneously addressing radar sensing needs.

Evaluation of the sea surface characteristics from remote sensing data by signal analysis methods is of high demand in a variety of applications ranging from marine navigation to ecological monitoring. Here we present experimental results demonstrating the retrieval of the sea surface characteristics from the backscatter signals obtained by slightly modified Doppler SHF radar. Based on a series of experiments we show explicitly that the sea surface monitoring in the coastal zone of about 1 km can be performed by a proposed experimental setup with reasonable accuracy and performance. Moreover, based on a particular series of measurement, we demonstrate how the sea waves velocity field can be reconstructed using a two-dimensional Fourier transform based approach and further analyzed to reveal the contributions of particular wave components.

The generation of synthetic environments is of prime importance for radar performance prediction and radar development. This is the case for maritime radar where realistic sea clutter generation is particularly useful. New detection strategies of small targets in high sea states with very long integration times, as well as the advent of affordable fixed-panels AESA, require adapting the sea clutter generation principles that were used with the previous mechanical scanning radars. This paper presents a method for synthetic clutter generation putting emphasis on a realistic clutter correlation properties reproduction, whether the beam movement is continuous or discontinuous, scanning very rapidly, randomly and even if the antenna beam is stationary.

This paper investigates the joint exploitation of Wi-Fi based Passive Bistatic Radar (PBR) and Wi-Fi based Passive Source Location (PSL) for drone localization. The inherent features of the two strategies and the results obtained from their comparison on experimental data show an interesting complementarity between them. Following this consideration, a proper sensor fusion strategy combining these two methodologies is investigated in order to achieve improved results in terms of positioning capability. The three strategies (PBR, PSL and sensor fusion) are evaluated against experimental data. The comparison between the use of the sensor fusion approach and the localization based on a single sensor (PBR or PSL) shows the benefits coming from the exploitation of multiple sensors.

In this paper the performance of the Unscented Kalman Filter (UKF) based tracking is investigated for different Sense and Avoid (SAA) flight scenarios. The improvement of the tracking accuracy through integrating the range rate information into the estimation process with UKF is illustrated. The robustness of this method is further evaluated with a data set provided by Airbus, simulating a range of typical approach scenarios with a detection angle of -110° to +110°.

Trajectory prediction and optimization capabilities are considered as crucial part for efficient Air Traffic Management (ATM) operation. One of the key factors that influence onto trajectory prediction is weather situation at the departure and arrival points and along the flight route. In this context it is crucial to utilize widely systems of operative obtaining information about weather hazards for short-term flight trajectory correction. Onboard meteorological radars are powerful and convenient tool for operative data obtaining during the aircraft flight when atmospheric and weather disturbances arise. In this paper possibilities of trajectory correction by providing accurate and operative meteorological data using the onboard radar system are shown and discussed.

A radar task scheduling method, dual-side scheduling (DSS), is proposed in this paper. In this method, the radar tasks are firstly received as an original sequence, then the time window for the task execution is separated into two sides. All the tasks at each side are shifting toward a separator, connected each other head-to-tail without dwell overlaps. The separator is placed at one of pre-set locations, and the random shifted start time (RSST) technique is applied in order to finalize the scheduling: the start time of each task is randomly shifted in its schedulable interval, then the DSS is respectively conducted at each separator. The RSST process is repeated many times, and the resulting schedule with the minimal cost among all attempts is the final solution. Over a broad range of task loading rate, the proposed method shows 1.5 to 6.2 times less costly than the earliest start time (EST), which is a widely used one-side scheduling method. A full cycle of DSS takes a few tens of milliseconds, short enough for real radar applications.

A multistatic active surveillance radar system has been developed under the project name SAMURAI Swiss African MUltistatic Radar Initiative). The system comprises of one TX node and two RX nodes and works at C-band frequencies. A phased array on transmit and digital beamforming on receive enable the radar's scanning capabilities. The system was tested in a two-weeks period taking place in November 2019 in Thun, Switzerland. The system was initially tested in the laboratory, followed by field tests with a radar target simulator and finally a series of drone flights were executed. A specific C-band multistatic target simulator was built in order to fully exploit the system's capabilities. The system allowed to fully test the Doppler accuracy and resolution, Range accuracy and resolution as well as the radar's detection capabilities for different target RCS'.

In recent years passive radar systems research has been increasingly focused on the use of satellite opportunity signals, and DVB-S signals in particular, since these offer virtually global coverage. Several papers have been published recently proving the effectiveness of very simple demonstrators based on COTS. However, conventional architectures struggle to employ coherent channels on the receiver impacting directly in their cost. In this work we show preliminary results for ground targets obtained using a very low-cost non-coherent COTS architecture.

Passive Radars (PRs) are promising emerging technologies to face new security requirements. Satellite illuminators are of great interest due to their nearby global coverage and availability, operating frequencies and waveforms. The main challenges are related to high transmission losses, which limit the coverage areas. An study of DVB-S capabilities as IoO is presented and first results of ground targets detection in a semi-urban scenario are presented. The employment of commercial parabolic antennas for acquiring both the reference and surveillance channel limits the angular coverage and therefore, the scenario of the PR. Results confirmed the feasibility of DVB-S PRs for low range ground target detection and tracking, and pointed out the effects of target echo Doppler spreading along the signal processing chain, whose analysis is a key step towards the proposal of solutions to increase detection performance.

This paper presents the results of passive synthetic aperture radar (PSAR) imaging obtained with barycentric back projection algorithm (BBPA). The main idea of this algorithm is to minimize the number of the ranges of raw radar data used in image reconstruction. The used solution allows to significantly reduce the number of calculation comparing to classical back projection algorithm (BPA) and is easily parallelizable. These opportunities give ability to create a compact PSAR system with SDR device as an analog to digital converter and mobile GPU platform as a processing unit. The used components due to small dimensions facilitate installation on the airplane platform. The presented in this paper results have been obtained using the PSAR data collected within recent APART-GAS measurement campaign which was held on 3-13 September 2019 in Poland. The work described in this paper may contribute to build future PSAR system working in real time conditions.

Synthetic Aperture radar (SAR) is widely used for earth ground imaging and mapping. In most cases the SAR radar is an active device and can be mounted on both air- and spaceborne platforms. Passive SAR imagery based on illuminator of opportunity such as DVB-T, WIFI, or active radar transmitters has been gaining attention recently and some experimental works has been already been shown recently by researchers to public. Simultaneous Active and Passive SAR imaging is the next natural step of development of this technology. In this paper a system which consist of two demonstrators which operate together in both active (C band) and passive (DVB-T band) mode is presented. The first preliminary results of active and passive SAR imaging of the same ground area taken in the same time using small airborne platform have been shown.

This paper presents Electronically Reconfigurable Superstrate (ERES) antenna capable of modifying the shape of the radiation pattern in an uncomplicated way. The approach adopted in this concept is based on switching the state of passive patch elements placed on an additional layer located above a simple microstrip patch antenna. In order to change the area covered by the antenna range, the proposed antenna provides six different configurations with different directions of maximum radiation and various 3 dB antenna beamwidth. The antenna is dedicated to working in the field of Ultra High Frequency (UHF) Radio Frequency Identification (RFID) applications.

Design and numerical characteristics of X-band non-planar full-metal slot reflectarray antenna are presented. The relative bandwidths of 19.6% upon a criteria of 3 dB directivity reduction and 31.2 dB peak directivity are obtained for the proposed reflectarray. The designed reflectarray size is 20λ×20λ and it consists of two panels assembled edge to edge that form non-planar surface. The proposed full-metal reflectarray design allows the use of laser-cutting techniques for antenna manufacturing. Comparison of the proposed non-planar reflectarray with optimized in different frequency range planar ones and a parabolic reflector is carried out.

Low RCS and long range target detection requires larger power aperture product, which can be achieved by phased array antennas with large number of elements. Antennas with Phased arrays with large antenna arrays increases system complexity. Subarray level multibeam architecture with array processing reduces the system complexity and improves the target detection and estimation performance. Subarray configuration plays a vital role in the array processing. In this paper a new framework with multibeam synthesis is proposed along with subarray configuration design methodology. Modified Clustering algorithms are developed to design the optimal subarray configuration. Experiments are conducted with large hexagonal planar array and results are evaluated with several performance metrics to demonstrate the significance of proposed methods

We consider DoA estimation in a monopulse radar system employing a tilted rotating array. We investigate the case of nonzero steering angles, in which case the mapping between the target's azimuth and elevation in the global coordinate system and their counterparts in the array local coordinate system becomes increasingly nonlinear and coupled. Since estimating the azimuth using coherently integrated signals might be difficult because of strong modulation in the difference signal induced by the rotation of the antenna, we develop an iterative approach that alternates between estimating the elevation using coherently integrated signals and estimating the azimuth using unfiltered signals. We also develop a simplified version of the scheme, which employs only one iteration and forms the final estimates by applying simple corrections to results of the first iteration.

Different approaches to development of an auxiliary antenna designated for sidelobe blanking systems are proposed and discussed. In the proposed concepts a set of two antennas having different radiation patterns is utilized in order to ensure good coverage of main radar antenna's sidelobes. The concepts of the auxiliary antenna are evaluated and compared. The results are comprehensively presented and the criteria for selection of the concept are reported.

Synthetic aperture radar (SAR) is widely used for ground and structure imaging, both in two and three dimensions. The author is working on a three-dimensional (3D) imaging method that aims to reduce the flight time and the amount of data collected through the calculation and optimization of a complex radar carrier trajectory, which is a computationally heavy process. This paper proposes a method of pre-calculating the point spread functions (PSF) for specific potential aperture points that can be used later to estimate the PSF for a trajectory, allowing for efficient trajectory optimization. Three coordinate systems are considered and compared in terms of computational complexity and accuracy, and have been proven to be usable in certain applications. The proposed method can facilitate the development of 3D SAR.

Regularized iterative reconstruction algorithms for Synthetic Aperture Radar (SAR) Tomography (TomoSAR), like the ones based on Maximum Likelihood (ML), offer an accurate estimate of the Power Spectrum Pattern (PSP) displaced along the Perpendicular to the Line-of-Sight (PLOS) direction. The recovered PSP is considered as 'good-fitted' or 'appropriate-fitted', since the reconstruction fits correctly enough with the position and density of the objectives in the field backscattered towards the sensor. However, the correct functioning of these regularization approaches is constrained to the proper selection of the regularization parameters. Therefore, for such a purpose, this paper suggests using a criterion based on the Stein's Unbiased Risk Estimate (SURE) strategy. SURE approximates the Mean Square Error (MSE) between the estimated and actual PSP, purely from the measured (observed) data, without the need of any knowledge about the true PSP. Consequently, the proper selection of the regularization parameters corresponds to the minimum SURE value, which guarantees having a 'good-fitted' reconstruction. The experiments are performed in simulated data for different representative cases.

The time and phase synchronization are the important issues that must be addressed for bistatic synthetic aperture radar (BiSAR). The processing of synchronization is discussed in the paper. First, the synchronization scheme of LuTan-1 system is introduced in detail. The test results of ground validation system are illustrated to verify the synchronization scheme in LuTan-1. Then, an algorithm based on frequency offset estimation and iteration processing is also proposed for the noncooperative BiSAR. The proposed algorithms have great application potential for future BiSAR system.

The road surface roughness directly influences the grip and skid resistance of the vehicles. Since these parameters are relevant for the safety of the road users, they have to be continuously monitored to keep track of its changes. The potential of airborne polarimetric SAR to remotely monitor the road surface roughness is investigated in this study using fully polarimetric X-band data acquired with DLR's airborne radar sensor F-SAR. The polarimetric analysis revealed that the anisotropy and coherency matrix (T3) elements are sensitive to the road surface roughness. Additionally SAR backscatter based empirical models for surface roughness estimation were investigated.

Phase noise (PN) is one of the most significant impairments adversely affecting the detection performance of frequency-modulated continuous wave (FMCW) radar systems. Due to the rapid advance of advanced driver assistance systems (ADAS), virtual testing and the evaluation of highlyautomated driving (HAD) functions became indispensable. In this work, the impact of PN on the performance of automotive radar sensors is demonstrated on HAD functions in a virtual driving simulator. Therefore, a PN model initially developed for static objects is applied to dynamic scenarios including moving objects. By implementing a real world scenario in the virtual environment the influence of PN on the detection performance of the radar sensor is demonstrated. The virtual test scenario is implemented using the CarMaker test driving software, which is commonly accepted as an accurate and reliable tool by the automotive industry. The radar sensor model including PN is implemented as a functional mock-up unit (FMU) using the standardized functional mock-up interface (FMI) 2.0 and the open simulation interface (OSI) 3.0.0. Finally, the radar FMU model simulations are compared with hardware measurements.

For in-depth validation of automotive radar sensors tailored radar test systems are required. Radar echo generators are core elements of those test systems and generate artificial objects with a certain distance, velocity, size and angular direction for evaluating the performance of radar sensors with respect to a known reference. With state-of-the-art sensors that use modern and sophisticated signal processing and modulation schemes, new challenges regarding test and validation setups occur. Especially the generation of artificial reference objects for MIMO radar sensors is challenging, due to the large aperture of the typically utilized phased array and the high sensitivity of this sensors regarding phase deviations. This paper investigates the effect of measurement geometries and the antenna configurations of radar echo generators on the measured angular accuracy of automotive radar sensors that rely on MIMO radar signal processing algorithms. The paper concludes with recommendations for MIMO radar test setups that incorporate radar echo generators.

Modern cars are equipped with many comfort and safety functions like for example Blind Spot Detection (BSD), Lane Change Assist (LCA) or Auto Cruse Control (ACC). Sensors used to support those functions are radars, cameras, ultrasonic and lidar. The forecast is that more and more cars in the future will be equipped with multiple sensors. Automotive radar is an important sensor that provides high quality measurement of range and velocity independent on weather conditions and sun illumination. The expectation is that the amount of cars equipped with radar sensors will increase as functions will be available not only for premium but also for middle price cars and with development of quasi-autonomous and autonomous driving. The number of radar sensors on a single car will also increase as more and more functions are supported by radar. With the increasing number of radar sensors on the road, the topic of interference mitigation will gain more importance. Publicly funded project IMIKO-Radar - Interference Mitigation by Cooperation in Radar for Autonomous Electric Cars investigates automotive interference and various mitigation possibilities. In this paper we will describe automotive radar interference measurements and present first results.

When integrating automotive frequency modulated continuous wave (FMCW) radar sensors for driver assistance systems into the vehicle, the radar sensor cover must be taken into account. Particularly metallic paints on polymer covers lead to high reflections, which impair the radar performance. Therefore, paint properties, which may influence the electromagnetic wave radiated by the sensor, have to be analyzed in realistic experimental setups. Within this paper we show by measurements around 80 GHz that the relative permittivity increases exponentially with increasing pigment volume concentration of the metallic pigments. In general, finer metallic pigments lead to higher relative permittivities. However, very fine pigments may agglomerate and therefore show behavior comparable to coarse pigments. In addition we could show that the type of painting method must be taken into account.

Density Based Spatial Clustering of Applications with Noise (DBSCAN) is the widely used clustering algorithm for automotive radar applications. Many modifications have been proposed across literatures. This paper discusses the most effective method of DBSCAN implementation for High resolution radar applications. Modification of the DBSCAN algorithm for computation and memory optimization especially for an embedded application is discussed in detail in this paper

A 94 GHz frequency-modulated continuous-wave radar that is regarded as a base for creating a focal-plane array imaging system has been developed. The key component of the radar is an original receiver module of a simple design and with low local oscillator power requirements. The radar prototype is described and demonstration of its operation capability is presented. The problems of developing a focal-plane array radar are discussed.

This paper presents the design and realization of a Doppler radar system based on a direct digital synthesizer (DDS) operating at 18.5 GHz. The Doppler radar presented here relies directly on the signal generated by the DDS. This represents a major difference to other radar systems, where a DDS is used only for PLL stabilization of a VCO. The specification of the DDS as well as the design of the radar system will be presented here. First Doppler radar measurement results in the frequency band from 5-10GHz will be shown using a speaker membrane as a target oscillating with a frequency of up to 100Hz. The radar system shows excellent performance with a low noise floor and the ability to resolve small frequency differences down to 0.3 Hz. It is also demonstrated that the radar exhibits a perfectly linear ultra-wideband tuning characteristics, which eliminates the need for VCO tuning linearization.

Algorithms for detection and selection of objects of interest in remote sensing observations based on multi-threshold processing are investigated. The studied algorithms convert monochrome images into a set of binary layers which are next subjected to simple morphological analysis allowing for the selection of isolated objects in each layer. By analyzing the location and the geometric characteristics of objects in neighboring layers one can generalize the selection procedure by applying objective geometric criteria to the multi-layer scene reconstruction based on the percolation effect. This way adaptive threshold can be selected individually for each object of interest leading to a significant reduction in the false alarms rate during detection especially at lower-level thresholds where high hit rates can be achieved. The efficacy and performance of the approach is supported using both simulated random fields as well as television and radar remote sensing observations.

The amount of space debris orbiting around the Earth has seen a dramatic growth through the recent years. This growth is fed by an avalanche multiplication process. In fact, according to the ''Kessler syndrome'', any collision generates more debris that then collide with other objects and produce further debris. This growth represents a serious hazard for operational spacecraft, human activities in space and even the Earth environment since their re-enter is uncontrolled. Thus, it is important to continuously monitor and characterize them. Instrumental features for their characterization are surely represented by their size and spin rate. Inverse Radon transform (IRT) tool has been proved to be a valid solution for this task. In this paper, we propose a comparison study between different approaches based on IRT for the estimation of the object's rotation period.

The paper presents the results of studies on analysis, implementation and testing of beamforming methods which can be used for enhancement of radiolocation capabilities of radioastronomical LOFAR station in the context of its use for passive radiolocation. Using the LOFAR system for passive radiolocation might be an highly cost-effective solution for location of objects due to the fact that most of the necessary equipment already exists. In this paper the location of planes by a single LOFAR station in Borowiec was considered as the proof of concept for a more complex system for localizing space objects in the future. The beamforming Phase-Shift algorithm used for passive radiolocation by means of LOFAR station was presented and thoroughly discussed. Beam patterns of steered antenna array of a LOFAR station and its single subapertures, known as tiles, were shown. Occurrence of grating lobes in presented beam patterns is also discussed. The results of preliminary experiments performed with real signals registered by the LOFAR station in Borowiec confirm the efficiency regarding enhancement of radiolocation capabilities, increasing radar's range and certainty of detection by means of beamforming.

We would like to invite all the participants of the conference to join the presentation about emotions in our life, and how to deal with them and as a result manage stress.

Emotions are states connected with pleasure or unpleasantness. They are also reactions to the positive or negative stress. We can describe emotions of human beings and animals, and perhaps - also plants.

In general, it is common to believe negative emotions are bad, but we shouldn't forget that they have also positive energy. If our different needs are not fulfilled from the early childhood we don't have the mechanism to develop many emotions at certain level. That could lead us to various psychical and physical illnesses and as a consequence to shorter life expectancy. Therefore it is very important to form our psychological resiliency to stres. That is why special Ego Resiliency Scale was created by Block and Kremen in 1996. Moreover the mechanism of the positive desintegration described by Kazimierz Dąbrowski enriches all human life and broadens horizons of thinking and feeling and can become the inspiration to the creativity in different domains.

The research on Mirror Neurons by Giacomo Rizzolatti is vital in the process of emotion's "contamination". Nowadays, due to the technical progress, many various experiments in this area are carried out with the help of optogenetics e.g. by Phd. Ewelina Knapska from Nencki Institute.

Emotions can cause psychosomatic illnesses, addictions and anyone can be object of manipulations because of emotions. We would like emphasize that the appropriate diet and exercises help us to deal with emotions and influence our behavior in a positive way.

Highly automated driving functions currently often rely on a-priori knowledge from maps for planning and prediction in complex scenarios like cities. This makes map-relative localization an essential skill.

In this paper, we address the problem of localization with automotive-grade radars, using a real-time graph-based SLAM approach. The system uses landmarks and odometry information as an abstraction layer. This way, besides radars, all kind of different sensor modalities including cameras and lidars can contribute. A single, semantic landmark map is used and maintained for all sensors.

We implemented our approach using C++ and thoroughly tested it on data obtained with our test vehicles, comprising cars and trucks. Test scenarios include inner cities and industrial areas like container terminals. The experiments presented in this paper suggest that the approach is able to provide a precise and stable pose in structured environments, using radar data alone. The fusion of additional sensor information from cameras or lidars further boost performance, providing reliable semantic information needed for automated mapping.

This paper presents a detailed investigation of the scattering mechanisms occurring at different traffic signs and a guide post in the 77 GHz automotive radar frequency band. By utilizing a polarimetric ISAR imaging process the scattering centers are spatially resolved in a 2D image plane. The proposed phase drift compensation approach provides the basis for a valid analysis of scatterers. A potential vehicle self-localization relying on such landmarks will benefit from this knowledge.

When adapting SAR (synthetic aperture radar) techniques to vehicles it becomes obvious, that there are some dramatic differences to air-born SAR systems. The main difference in automotive applications is, that vehicles does not drive with constant speed in straight direction only as planes do. Therefore in this paper a novel algorithm is developed what enables to estimate vehicles ego motion very precisely and at exactly those time steps when it is needed. This algorithm enables both, generating SAR maps as well as autarkic ego motion estimation. Tests in real traffic scenarios show promising results.

Fundamentally, automotive radar sensors with Digital-Beamforming (DBF) use several transmitter and receiver antennas to measure the direction of the target. However, hardware imperfections, tolerances in the feeding lines of the antennas, coupling effects as well as temperature changes and ageing will cause amplitude and phase errors. These errors can lead to misinterpretation of the data and result in hazardous actions of the autonomous system. First, the impact of amplitude and phase errors on angular estimation is discussed and analyzed by simulations. The results are compared with the measured errors of a real radar sensor. Further, a calibration method is implemented and evaluated by measurements.

In automotive radar applications, the compressive sensing (CS) based DoA estimation is used in array signal processing in recent years. Sparse reconstruction has the potential to estimate the direction of arrival (DoA) with super resolution. However, failed results may be acquired via sparse reconstruction in inappropriate conditions, namely the critical condition determining success or failure must be taken into consideration. In this paper, the sparsity of the scenario and the signal-to-noise ratio (SNR) are analyzed as the main factors via phase transition diagrams. Other factors affecting the success or failure are also investigated, such as the array configuration and the sparse recovery algorithm. Simulated and experimental results demonstrate the critical conditions, in which the DoA estimation is successful or failed.

A new architecture for a widely distributed dual-band coherent multiple-input multiple-output (MIMO) radar system is illustrated, and its implementation and testing are reported. The system consists in a central unit based on a single mode-locked laser, supporting multiple remote radar nodes linked by standard optical fiber pairs. Every remote node operates both in the S- and X-band, and it can be displaced over distances of several kilometers, allowing to monitor a scene under different angles of view. All the remote nodes share the same oscillator and digital signal processing unit, both located in the central node. This architecture allows to perform centralized data fusion on the signals acquired by the remote nodes, and, by virtue of the system coherence, to take advantage of the coherent MIMO processing strategy thus to offer a superior spatial resolution, which is even magnified by the dual-band approach.

A method of 3D velocity measurement based on an integrated MIMO radar is presented. The method is based on cross-correlation in range and cross-range, making use of the spatial distribution of the antenna aperture. Using measurement data 3D velocity measurement with a relative error of less than 5% is shown being suitable to compensate for drift effects which limit the performance of IMU based motion detection systems.

The article deals with the technology of construction of nonparametric processing methods of correlated random processes. The use of a Markov model of correlated signals allows to synthesize the nonparametric rank algorithms. The theory of synthesis of nonparametric rank Markov decision rules is constructed, the problem of synthesis of rank nonparametric algorithm for detection of correlated signal against the background of uncorrelated noise on the output of amplitude demodulator is solved. Property of this algorithm is investigated

One of the primary challenges for an Electronic Support (ES) receiver is interception and analysis of low probability of intercept (LPI) radar signals, which for example are linear frequency-modulated (LFM) signals. In the paper detection and estimation of LFM waveform parameters based on the extended forms of the standard cubic phase function (CPF) is proposed. Originally the CPF function was introduced for instantaneous frequency rate (IFR) estimation. Extended forms are created by summation operations or multiplication operations, or integration operations of the time slices of the standard CPF function. The CPF function and its extended forms concentrate energy of LFM waveforms along a IFR line in the time-chirp domain just as the short time Fourier transform (STFT) and Wigner-Ville distribution (WVD) concentrates energy of LFM signals along an instantaneous frequency (IF) line in time-frequency domain. Based on the extended forms of the standard CPF function, test statistics have been proposed and intensively evaluated in Monte-Carlo simulations. Selected results of investigations on parameter estimation and high detection efficiency obtained by the proposed methods are presented.

High frequency Over-the-Horizon Radar (OTHR) provides an economical means to track non-cooperative air targets over large expanses of land and ocean. Because of dynamic ionospheric conditions in polar regions, any OTHR would necessitate a system where the operating frequencies and elevation angles change periodically to maintain constant detection of targets downrange. In this regard, an accurate electron density model is necessary for the purpose of improving operational OTHR and OTHR planning/design. Observations over recent years have established that large-scale electron density structures are a common feature of the polar cap F-region ionosphere. These structures take the form of convecting patches and arcs of enhanced electron density which form tilted reflection surfaces for HF radiowaves, allowing off-great circle propagation paths to be established. Numerical ray tracing has been employed to simulate the effects of these structures on the ray paths of the radiowaves. The effect of frequency monitoring system for OTHR due to the presence of patches of enhanced electron density within the polar cap ionosphere has been studies in this paper.

Modern linear particle accelerators are large-scale facilities utilizing normal and superconducting microwave resonator cavities to increase energy of physical particles such as electrons or protons. Particles travel at velocities comparable to the speed of light through the cavities and high-gradient Electro-Magnetic fields must be extremely precisely amplitude and phase controlled in order to assure proper acceleration of the particle beam. Sophisticated accelerating field controllers and beam diagnostic systems require synchronization reaching tens of femtoseconds in time domain or 0.001 degree in phase at RF frequencies. In larger accelerators like the E-XFEL in Hamburg, there are several thousands of synchronized devices distributed along 3,4 km long machine. This talk will cover challenges and solutions used to distribute RF synchronization signals in large scientific machines, including control of phase noise and phase drift in components of the synchronization system.