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International audience; In this paper, a novel method to improve the readability of chipless tags is presented. When the EM wave falls upon the tag's surface at normal incidence or with a known incidence, the proposed approach permits to obtain a higher signal-to-noise ratio (SNR) of resonators whose orientation with respect to the normal to the plane in which the tag is positioned is unknown and thus, to increase the reading distance of the tag. It introduces a technique based on the detection of this tag orientation in relation to the antennas; a projection of the signals will allow to correct this misalignment in order to always be able to decode the tag identifier on a signal that corresponds to an ideal alignment between the tag and the antennas. With this principle, it is also possible to separate the resonance mode of the resonator that is connected to the identifier from other parasitic resonance modes that may appear due to a possible misalignment between the tag and the antenna. This principle is applied to loop resonators commonly used in chipless RFID which can present strong parasitic modes of resonance. Also, this method makes the reading orientation invariant, allowing to read the resonator whatever its orientation with respect to the normal to the plane in which the tag is positioned. Likewise, the proposed method can be also used to sense this resonator orientation. This method requires a dual-polarization antenna and a 2-ports vector network analyzer (VNA). Results are validated in simulation and with real-environment measurements for a single resonator as well as for multiple resonators, as it is classically used in the chipless RFID technology. Measurements in a harsh environment, as well as comparisons with classical techniques such as time gating, are presented. A study on the improvment of the read range is achieved to highligth the potential of the proposed technique. A reading distance of more than 80cm was thus obtained, which represents 20cm more than with the classic use of a post-processor based on time gatting. Finally, the principle of the measurement is generalized by applying it to a tag with a ground plane and considering that the antenna is not necessarily placed in normal incidence with respect to the plane of the tag.

The integration of wireless sensors into the automotive industry is making vehicles increasingly safe and autonomous. At present, vehicles are equipped with external sensors that facilitate maneuverability and braking and internal sensors that detect presence, seat belt state, and occupant vital signs. Early detection of dysfunctional breathing patterns can reduce the risk of accidents caused by drowsiness or fatigue. In this regard, this work presents an MIMO FMCW Radar System able to distinguish dysfunctional breathing patterns from human torso motion. The torso has been divided into six regions, and the amplitude of the elongation and the frequency of motion of each region have been measured during breathing. An elongation map is then constructed in order to graphically show the dysfunctional breathing patterns. The signal processing includes a peak search algorithm to detect elongation amplitude and a bandpass frequency filter to minimize dc components, random driver motion, and vehicle vibration. A torso elongation emulator phantom has been assembled with materials of skin-like relative permittivity and dc motors for calibration and validation of basic breathing patterns. Finally, the signal of the system is compared with that of a commercial respiration belt, and then the system is tested by performing measurements on people. The MIMO radar system is able to measure, differentiate, and classify patterns associated with dysfunctional breathing such as hyperventilation syndrome and thoracic dominant breathing. This work was supported in part by the Spanish “Comision Interministerial de Ciencia y Tecnologia” (CICYT) under Project PID2019-107885GB-C31 and Project MDM2016- 0600, in part by the Catalan Research Group under Grant 2017 SGR 219, and in part by the “Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación” (SENESCYT) from the Ecuadorian Government

The ambiguity problem of targets in Doppler beam sharpening (DBS) with forward-looking radar is considered. While DBS is proposed earlier to improve the angular resolution of the radar while keeping the antenna aperture size limited, such a solution suffers from ambiguities in the case of targets positioned symmetrically with respect to the platform movement. To address this problem, an approach named unambiguous Doppler-based forward-looking multiple-input multiple-output (MIMO) radar beam sharpening scan (UDFMBSC) is proposed, based on the combination of MIMO processing and DBS. The performance of the proposed method is compared to existing approaches using simulated data with point-like and extended targets. The method is successfully verified using experimental data.

Linked to the increasing availability of datasets for radar-based human activity recognition (HAR), in this Student Highlights contribution, we report on a classification project that a group of 23 graduate students performed at TU Delft. The students were asked to work in groups of 2-3 members and to use the publicly available University of Glasgow dataset to develop the best classification pipeline as possible. This involved development and justification of both choices for the preprocessing techniques on the radar data (e.g., time-frequency distributions and cleaning of the signatures), and for the classification algorithms (e.g., the type of the algorithm, the hyperparameters' selection, the training-validation-testing split). While this student activity was performed at a small scale and with educational rather than research aims, we are happy to report it to the AESS readership, as we believe that such initiatives with open datasets sharing and classification algorithm benchmarking are beneficial for the wider radar research community. Furthermore, a list of publicly available datasets for radar-based HAR that can be used for similar initiatives is also reported in this article.

Radar-based gesture recognition can play a vital role in autonomous vehicles’ interaction with vulnerable road users (VRUs). However, in automotive scenarios the same gesture produces strongly differing radar responses owed to the wide range of variations such as position, orientation, or ego-motion. Since including all kinds of modifications in a measured dataset is laborious, gesture simulations alleviate the measurement effort and increase the robustness against edge and corner cases. Hence, this paper presents a flexible geometric human target model allowing the direct introduction of a wide range of modifications, while it facilitates the handling of shadowing effects and multiradar constellations. Using the proposed simulation model, a dataset recorded with a radar sensor network consisting of three chirp sequence (CS) radars is resimulated based on motion data simultaneously captured with a stereo video system. Completely substituting the measured by simulated data for training, a convolutional neural network (CNN) classifier still achieves 80.4% cross-validation accuracy on a challenging gesture set, compared to 89.4% for training on measured data. Moreover, using simulated data the classifier is shown to successfully generalize to new scenarios not observed in measurements., acceptedVersion

This article considers the detection and tracking of weak targets in multiple pulse repetition frequency (multi-PRF) radars using the track-before-detect (TBD) technique. By exploring the measurement independence among different PRFs, we decompose the joint multi-PRF and multiframe optimization problem into several lower dimensional maximizations, each of which corresponds to an intra-PRF multiframe processing. An efficient two-stage TBD procedure with a parallel structure is proposed for the multi-PRF radars. Specifically, in the first stage, a constraint inequality is derived analytically and used to decouple the measurement ambiguities from the nonlinear conversion relationship between polar and Cartesian coordinates. The intra-PRF multiframe integration can then be carried out concurrently using the ambiguous measurements and the target-like measurement plot sequences with different ambiguities are extracted for different PRFs. In the second stage, a covariance combination fusion-based inter-PRF joint disambiguation and estimation algorithm is proposed to solve the ambiguities of the plot sequences and output high-Accuracy target tracks. Simulation experiments show that the proposed algorithm can provide a good detection performance and higher tracking accuracy with much lower complexity. This work was supported in part by the National Natural Science Foundation of China under Grant 61771110, Grant U19B2017, and Grant 61871103, in part by the Fundamental Research Funds of Central Universities under Grant ZYGX2020ZB029, in part by Chang Jiang Scholars Program and the 111 Project under Grant B17008, and in part by the China Scholarship Council.

Microwave imaging has been investigated for medical applications such as stroke and breast imaging. Current systems typically rely on bench-top equipment to scan at a variety of antenna positions. For dynamic imaging of moving structures, such as the cardiovascular system, much higher imaging speeds are required than what has thus far been reported. Recent innovations in radar-on-chip technology allow for simultaneous high speed data collection at multiple antenna positions at a fraction of the cost of conventional microwave equipment, in a small and potentially portable system. The objective of the current work is to provide proof of concept of dynamic microwave imaging in the body, using radar-on-chip technology.Arrays of body-coupled antennas were used with nine simultaneously operated coherent ultra-wideband radar chips. Data were collected from the chest and thigh of a volunteer, with the objective of imaging the femoral artery and beating heart. In addition, data were collected from a phantom to validate system performance. Video data were constructed using beamforming.The location of the femoral artery could successfully be resolved, and a distinct arterial pulse wave was discernable. Cardiac activity was imaged at locations corresponding to the heart, but image quality was insufficient to identify individual anatomical structures. Static and differential imaging of the femur bone proved unsuccessful.Using radar chip technology and an imaging approach, cardiovascular activity was detected in the body, demonstrating first steps towards biomedical dynamic microwave imaging. The current portable and modular system design was found unsuitable for static in-body imaging.This first proof of concept demonstrates that radar-on-chip could enable cardiovascular imaging in a low-cost, small and portable system. Such a system could make medical imaging more accessible, particularly in ambulatory or long-term monitoring settings.

In-band full-duplex (IBFD) technology has the potential to not only double the communication throughput but also enable additional capabilities. The fusion of radar and communication subsystems is an excellent example of how IBFD facilitates integration of radar functionality into a communication system. Developing and analysis of a joint IBFD radar-communication (RadCom) system is at the core of this article. This system derives the range-Doppler image from the state of an adaptive filter, which already exists in a typical IBFD transceiver. Our approach is waveform-independent and reuses the radio frequency (RF) front-end while it requires little additional digital logic. The proposed system is prototyped to assess the modem-radar coexistence in a real-world IBFD communication link budget. Employing the prototyped system, we quantify the additional required logic resources and investigate whether such a RadCom approach dictates a tradeoff between the two intended functionalities. The experimental results show that the proposed solution enables a communication system to detect targets within 20 m while maintaining an IBFD link with another communication node, info:eu-repo/semantics/published

Deinterleaving mixtures of radar pulse sequences is the first and the most vital step for modern electronic reconnaissance systems to intercept and analyze the intentions of non-cooperative radars. Currently, these systems are facing great challenges due to the emerging complexity of radar modulations. This paper proposes a novel method for deinterleaving mixtures of radar pulse sequences based on the time series characteristics of each source (component pulse sequences). Firstly, the mathematical representations are established to describe the structural characteristics of each source. Then, the deinterleaving problem is formulated as a minimization of a maximum-likelihood cost function that can be solved efficiently through a supervised neural machine translation (NMT) network, i.e. to translate each received pulse in the interleaved pulse sequence to the corresponding source label. A sequence-to-sequence NMT model is proposed to capture the structural relationships among the non-adjacent pulses originated from the same source in the mixtures and assign the corresponding label to each pulse. The proposed method does not require the exact knowledge of each component pulse sequence. The experimental results based on the time of arrival sequence of mixed pulse sequences show that the proposed method outperforms the state-of-the-art deinterleaving methods and achieves satisfactory performance under highly non-ideal situations with measuring noise and lost pulse conditions. The proposed method can be directly applied to other fields involving deinterleaving problems and multi-variate input conditions.

In order to improve the speed of passenger screening while preserving the effective capability to detect more sophisticated threats, airport security imaging systems must be able to accurately characterize concealed body-worn objects. In addition to improving the passenger experience, this system capability will enhance airport security for the traveling public. This paper presents a real-time, fully-automatic algorithm for the wideband millimeter-wave (mm-wave) radar reconstruction of the nominal human body contours, even in the presence of an affixed weak dielectric object or when a portion of the body cross-section is not captured by the imaging scanner. The algorithm extracts the main contours from a noisy collection of 3D reconstructed reflectivity and approximates the nominal human body cross-section via fitting a low order angular Fourier series. This important step is essential for precise characterization of concealed body-worn explosives. A ranking algorithm is developed as a metric for the nominal body reconstruction accuracy. We verify the developed algorithm by applying it to the actual images of the High Definition-Advanced Imaging Technology (HD-AIT) system, a laboratory prototype mm-wave scanning system developed recently by the US Department of Homeland Security (DHS). The reconstructed body contours may be used to estimate the electric permittivity of the concealed person-worn objects.

A sequential decision process in which an adaptive radar system repeatedly interacts with a finite-state target channel is studied. The radar is capable of passively sensing the spectrum at regular intervals, which provides side information for the waveform selection process. The radar transmitter uses the sequence of spectrum observations as well as feedback from a collocated receiver to select waveforms which accurately estimate target parameters. It is shown that the waveform selection problem can be effectively addressed using a linear contextual bandit formulation in a manner that is both computationally feasible and sample efficient. Stochastic and adversarial linear contextual bandit models are introduced, allowing the radar to achieve effective performance in broad classes of physical environments. Simulations in a radar-communication coexistence scenario, as well as in an adversarial radar-jammer scenario, demonstrate that the proposed formulation provides a substantial improvement in target detection performance when Thompson Sampling and EXP3 algorithms are used to drive the waveform selection process. Further, it is shown that the harmful impacts of pulse-agile behavior on coherently processed radar data can be mitigated by adopting a time-varying constraint on the radar's waveform catalog., Comment: 16 pages, 9 figures. arXiv admin note: text overlap with arXiv:2010.15698

This paper presents a high-gain slotted ridge waveguide array antenna (SRWAA) with inductive diaphragms, which can realize a wide-sector beam with a low sidelobe simultaneously. The proposed antenna can cover a wide detection range and avoid interference from other directions. The expected excitation distribution for the antenna array is extracted through a beamforming method. To reduce the influence of the dispersion phenomenon on signal quality, inductive diaphragms are inserted into the sidewall of the ridge waveguide, which is fully analyzed from the point of the equivalent circuit. A cut-off-mode power divider is utilized, which can control the power ratio flexibly. A SRWAA working at 24.125 GHz, including a six-way feeding network, and a 6×24 slot array with the size of 330 mm × 66.8 mm is designed and fabricated. The measured sidelobe level (SLL) and half-power beamwidth (HPBW) in the elevation plane are -19.6 dB and 54.41°, with the counterparts in the azimuth plane -29.8 dB and 3.15°, respectively. The measured peak gain is 22.3 dBi at 24.125 GHz. The measured results are in good agreement with the simulated ones. This work has the potential to be applied in air detection, anti-unmanned aerial vehicles (UAVs), meteorological radar, and imaging radar.

Range-dependent clutter suppression is a challenging problem in non-sidelooking (NSL), bistatic, and conformal antenna array airborne radar, especially in the presence of range ambiguity. Superimposed stepped frequency (SSF) radar employs a small frequency increment across the stepped signals in each pulse, which induces a dimension related to slant range. In this paper, an airborne radar framework is established with SSF signal as the transmit waveform. Thus, a two-stage adaptive clutter suppression method is proposed which utilizes the degrees of freedom in range, space and time domains provided by airborne SSF radar. In the first stage, the secondary range dependence compensation (SRDC) approach is adopted to distinguish the clutter of each range region in the carrier frequency domain. Then, a target-free covariance matrix is estimated by the compensated data, and the covariance matrix is used for the range-ambiguous clutter separation in the carrier frequency domain. Thus, the space-time snapshot of each range region can be extracted. In the second stage, a clutter segmentation processing method is devised for residual clutter suppression.

A theoretical sea echo modeling of the floating-platform high-frequency hybrid sky-surface wave radar (HSSWR) is presented. The ionosphere is considered to be a no-tilt reflecting plane moving in the vertical direction. Subsequently, the first-order sea clutter cross section with consideration of the platform sway and yaw motion is derived. Simulations are conducted to explore the influences of the ionospheric movement and the platform oscillation motion on the sea clutter power spectrum. Simulation results indicate that the platform sway motion may induce additional peaks that distribute symmetrically concerning the Bragg peaks, while the platform yaw motion and the ionospheric movement may broaden even split the sea clutter. Experiments are conducted with the newly-developed HSSWR system, of which the receiving arrays are simultaneously deployed on a floating platform and the shoreside. Experimental measurements concerning the frequency shift, Doppler width, and the arrival angle of the E-layer/F-layer ionosphere reflected direct wave are compared and analyzed. The study demonstrates the feasibility of the proposed modeling and provides valuable guidelines for the sea clutter characteristics analysis and the data quality assessments of the floating-platform HSSWR.

The joint radar-communication (RadCom) concept has been continuously gaining interest due to the possibility of integrating radar sensing and communication functionalities in the same radio frequency hardware platform. Besides a number of challenges in terms of hardware design and signal processing, the choice of suitable modulation schemes plays a significant role in driving the performance of RadCom systems. In this sense, this article presents an overview of state-of-the-art modulation schemes for RadCom systems, namely, chirp sequence, phase-modulated continuous wave, orthogonal frequency-division multiplexing, and orthogonal chirp-division multiplexing. For each of them, a detailed system model is outlined, and parameters for quantifying both radar and communication performances are presented. Finally, a comparative analysis of the aforementioned RadCom modulation schemes is carried out to illustrate the presented discussion.

The vital sign measurement systems inside vehicles have taken great or impulse in recent years, and the technologies that have been most welcomed are based on wireless measurements that do not interrupt driving and are imperceptible to the driver. There are disorders in breathing patterns, which include the movement of different regions of the human thorax mainly. In this sense, the objective of this paper is to determine the dimensions of a lens-based antenna system and the pointing angles of the radiation main lobe of the six antenna-elements to measure the elongation of six regions of the human torso and determine breathing patterns. The pointing angle is controlled by the position of the antenna behind the lens, and the beamwidth of the lobe depends on the directivity achieved by the antenna. An electronic system to simulate torso elongation is also presented to calibrate and test the sensitivity of the system. This work was supported by the Spanish “Comisión Interministerial de Ciencia y Tecnologia” (CICYT) under projects PID2019-107885GB-C31 and MDM2016-O6OO; Catalan Research Group 2017 SGR 219; and ”Secretaría Nacional de Educación Superior, Ciencia, Tecnología e Innovación” (SENESCYT) from the Ecuadorian government.

When range ambiguity and range dependence coexist in forward-looking ground moving target indication (GMTI) radar, the traditional space-time adaptive processing (STAP) approaches may fail to work. To cope with this issue, a range-ambiguous clutter suppression approach based on elevation time diverse array (TDA) radar system and azimuth phase coding (APC) technique is presented in this paper. Due to the advantages of frequency scanning, the elevation TDA radar is able to cover all directions by transmitting a single time-shifted waveform. Therefore, a frequency bandpass filter is devised for each single range-bin to achieve the mainlobe echo extraction procedure. In the sequel, the azimuth phase decoding and Doppler filtering are performed to deal with the residual sidelobe ambiguous energy. With two-dimensional filtering, one can extract the unambiguous signals for each range region independently. Then, the traditional clutter compensation and STAP methods are employed to suppress the ground clutter. Finally, the effectiveness of the proposed framework in resolving range ambiguity are verified by the numerical simulation experiments.

Limited access to available spectrum motivates new age radio frequency (RF) systems to co-exist and cooperate. In this paper, we consider a joint communication and radar system (labeled Comm-Radar), that is capable of receiving and decoding communication signals while simultaneously enabling radar functionalities. Traditionally, systems that leverage principles of spectrum convergence, deemed each functions to be detrimental to the others. This has led to successive interference cancellations strategies that effectively isolate each of the functionalities. Here, in the context of Comm-Radar processing structure, we show that ambient communication transmissions actually assist in radar estimation. The insight is that communications multipath reflects off radar targets (we denote these comm-target paths) in the environment, and can be processed at the receiver to extract extra information. In this work we characterize the fundamental performance limits of such a joint system.To demonstrate the radar performance gain achievable via the processing of extra comm-target paths, the closed-form Cramer-Rao Bound (CRB) for the estimation of direction, range and velocity of a target is derived, for both the general case, and practical radar and communication signalling schemes. Based on the CRB, joint outer bounds are obtained to characterize the trade off between estimation performance and communication rate. Finally, numerical results verify the advantages of utilizing the target reflections from the communication signal to bolster radar performance.

International audience; A 3-in-1 depolarizing circular scatterer for the polarimetric radar calibration is proposed in this paper. The proposed scatterer is low cost, compact, planar circuit, and well suited for the radar operating in a compact range, for example, chipless RFID technology. By the virtue of its circular shape, the rear side of the proposed scatterer acts as a metallic disk with strong co polarization backscattered signals. The front side is composed of eight resonant dipoles which make it nondepolarizing and depolarizing scatterers at the inclination of 0° and 45°, respectively. The features of proposed circular scatterer are tested as reference calibration objects for single antenna based polarimetric radar calibration techniques. Two test objects are utilized: a dihedral tilted at 45° and a depolarizing multi resonant planar structure commonly called chipless RFID tag. The performance of proposed circular scatterer is also compared with the standard reference calibration objects: a metallic disk and a dihedral tilted at 22.5°. The performance of proposed circular scatterer is comparable to the standard reference calibration objects for the calibration techniques (namely Type 1 and Type 2). The proposed scatterer is potentially tolerant of displacement up to 1 cm and misalignment equals 2°.

In this paper, a joint design for cooperative spectrum sharing framework of multiple-input multiple-output (MIMO) radar and MIMO communication system in radar multi-target optimization is proposed. The interesting design Degrees of Freedom (DOFs) include radar transceiver beamforming vector and communication system codebook, whereby the designed problem is a constrained minimization of total radar effective interference power under power limited conditions and communication rate constraint guaranteeing both the two coexistence systems performance. As to the non-convex multi-variables problem, an alternating iteration approach is developed to solve the three suitably transformed subproblems, the closed form solutions are derived, and the convergence of the proposed design is guaranteed. Finally, numerical results show the spectrum sharing performance of the proposed approaches.

Near-field radar cross-section (NF-RCS) of a target depends on antennas’ radiation and can be maximized by adjusting the radiation patterns. It is justified by the power return ratio and can be computed by a comparison method. A theoretical foundation of operational mechanism for phased arrays of antennas is presented to produce conformal radiations for NF-RCS enhancement. The target’s scattering coefficients are extracted from operating the antenna array’s digital phase shifters to steer the resulting beams in this work. The scattering matrix is then analyzed by the singular value decomposition (SVD) to determine the antennas’ excitations for maximum NF-RCS with estimation stability. It results in orthogonal beams for the two-way radiations of antenna arrays to interpret the scattering mechanisms. The feasibility is validated by HFSS full-wave simulations and experimental measurement data.

Occupancy grids encode for hot spots on a map that is represented by a two dimensional grid of disjoint cells. The problem is to recursively update the probability that each cell in the grid is occupied, based on a sequence of sensor measurements from a moving platform. In this paper, we provide a new Bayesian framework for generating these probabilities that does not assume statistical independence between the occupancy state of grid cells. This approach is made analytically tractable through the use of binary asymmetric channel models that capture the errors associated with observing the occupancy state of a grid cell. Binary-valued measurement vectors are the thresholded output of a sensor in a radar, sonar, or other sensory system. We compare the performance of the proposed framework to that of the classical formulation for occupancy grids. The results show that the proposed framework identifies occupancy grids with lower false alarm and miss detection rates, and requires fewer observations of the surrounding area, to generate an accurate estimate of occupancy probabilities when compared to conventional formulations.

In the exploration of broadband radar absorbing structure (RAS), a new kind of multilayer gradient perforated RAS constituted of magnetic iron metal (Fe) and silicon carbide (SiC) is examined utilizing a top-down fabrication technique and metaheuristic grey wolf optimization (GWO) algorithm. The investigation of proposed structures and magneto-dielectric study of samples is carried out in 8.2 to 12.4 GHz (i.e., X-band). Distinct single and multilayered RASs are optimized using the GWO algorithm under certain restrictive conditions. In addition, the GWO algorithm is reinforced with a fitness function to acquire maximum bandwidth below -10dB threshold (RC≤-10 dB) in various oblique angles of incidence with a minimum coating thickness (t≤2.0 mm). Among all investigated RASs, triple-layer gradient perforated structure (TLGPS) is found to be effective which fulfills the lightweight, broadband, and angular stable behavior of an efficient absorber. TLGPS has considerably exhibited the concept of impedance gradient which assists in triumph broadband radar absorbing materials (RAMs) for low observable applications.

We demonstrate the efficacy of periodic corrugations, fabricated as part of the radar cover to serve the dual purpose of protecting the radar circuitry and maximizing transmission in millimeter-wave automotive radars. A 2-dimensional array of square-base pyramids engraved on the plastic radar cover was optimized to achieve minimum reflection for a wide range of incident angles, ± 40° and across the operating frequency band of 76 to 81 GHz. More importantly, we present an alternative radome texture, namely the inverse-pyramid corrugations that results in improved structural integrity as compared to the pyramidal corrugations. This novel inverse-pyramid radome structure is also much easier to manufacture and achieves similar performance as the more conventional pyramid structure. Both designs are shown to significantly reduce radar cover reflections, which is perhaps the most significant bottleneck in modern millimeter-wave automotive radar sensor performance.

Range/Doppler migration and velocity ambiguity are two well-known problems encountered in high-speed moving target detection using linear frequency-modulated continuous wave (LFMCW) automotive radar. To mitigate the problems, we introduce a simple Doppler-Range Processing (DRP) algorithm by first performing Doppler processing via fast Fourier transform (FFT) across slow-time samples, followed by a simple interpolation step, and then range processing via FFT along Doppler migration lines over fast-time samples. The proposed DRP algorithm can achieve full range and velocity resolutions, as well as full coherent integration gains. It attains a computational complexity comparable to that of the conventional 2D-FFT based Range-Doppler Processing (RDP) approach, computationally much more efficient than existing approaches. The proposed DRP algorithm can automatically resolve the velocity ambiguity problems. We analyze its velocity ambiguity mitigation capability in relation to the radar bandwidth and the number of slow-time samples within a Coherent Processing Interval (CPI). The effectiveness and the computational efficiency of the proposed algorithm are demonstrated by numerical examples.

This paper presents a radar cross-section (RCS)-based statistical recognition system for identifying/ classifying unmanned aerial vehicles (UAVs) at microwave frequencies. First, the paper presents the results of the vertical (VV) and horizontal (HH) polarization RCS measurement of six commercial UAVs at 15 GHz and 25 GHz in a compact range anechoic chamber. The measurement results show that the average RCS of the UAVs depends on shape, size, material composition of the target UAV as well as the azimuth angle, frequency, and polarization of the illuminating radar. Afterward, radar characterization of the target UAVs is achieved by fitting the RCS measurement data to 11 different statistical models. From the model selection analysis, we observe that the lognormal, generalized extreme value, and gamma distributions are most suitable for modeling the RCS of the commercial UAVs while the Gaussian distribution performed relatively poorly. The best UAV radar statistics forms the class conditional probability densities for the proposed UAV statistical recognition system. The performance of the UAV statistical recognition system is evaluated at different signal noise ratio (SNR) with the aid of Monte Carlo analysis. At an SNR of 10 dB, the average classification accuracy of 97.43% or better is achievable., Comment: one column, 39 pages

Marine X-band radar has been suggested to be capable of monitoring significant wave heights in both offshore and open sea areas. In contrast to studies on offshore radar, significant wave height estimations from coastal radar images, which exhibit complicated radar backscattering features, have received little attention. This study proposes a method for retrieving the significant wave height from coastal areas that are often influenced by nononshore winds. The square root of the signal-to-noise ratio in radar images has been widely applied to estimate the significant wave height. However, nononshore wind cases show a poor correlation between the square root of the signal-to-noise ratio and the in situ significant wave height. In addition, the spectral shapes from radar images in nononshore wind cases are very different from those in onshore wind cases. To improve the significant wave height estimations from coastal radar images, we implement an artificial neural network algorithm. After training and testing the algorithm, we confirm that the estimated significant wave heights are more reliable for both onshore and nononshore wind cases if the square root of the signal-to-noise ratio, power from nearshore radar subimages, and in situ wind components are included in the input layer of the neural network.

Coherent microwave radar, which is a rapidly emerging tool to sense waves, usually utilizes the orbit velocities extracted from either temporal or spatial radar echoes. The distribution of energy in the wavenumber-frequency spectrum is changed by some nonlinear features, and correspondingly, this kind of method always provides a significantly overestimated wave period. To address this problem, a novel inversion algorithm, which utilizes the spatial and temporal returns collected with a recently developed coherent S-band radar, is proposed for retrieving wave parameters. A 2-D Fourier transform is applied to the spatial-temporal matrix of velocities to estimate the wavenumber-frequency spectrum. Then the wavenumber-frequency spectrum is integrated over the wavenumber domain to obtain the 1-D velocity spectrum. And the wave height spectrum is estimated from the 1-D velocity spectrum by the direct transform relationship between the 1-D velocity spectrum and the wave height spectrum. Later, significant wave heights and mean wave periods can be derived by the zeroth and first moments of the wave height spectra, respectively. The algorithm is validated using simulation and real data. An approximately four-day dataset collected with a shore-based coherent S-band radar deployed at Beishuang island during a typhoon period is reanalyzed and used to retrieve significant wave heights and mean wave periods. Comparisons between the measurements of radar and wave buoy are conducted, and radar-derived and buoy-measured wave parameters are in a reasonable agreement with a coherent coefficient over 0.9. The results indicate that the proposed method is effective for wave measurements using coherent S-band radar.

Ship detection using polarimetric synthetic radar (PolSAR) imagery attracts a lot of attention in recent years. Most notably, the detector polarimetric notch filter (PNF) has been demonstrated to be effective for ship detection in PolSAR imagery, which gives excellent performances. In this work, a mathematical form of one new PNF (NPNF) based on physical mechanisms of targets and clutter is further developed for partial targets. The different mechanisms have been revealed based on the projection matrix. The experimental results including simulated and measured data demonstrate that the NPNF exhibits a better performance than the original PNF.

Ultrawideband (UWB) attracts extensive attention for the Internet-of-Things applications, especially the fine-grained location-based services. Rather than active tracking, this article explores the UWB-based device-free pedestrian tracking problem. Concerning the challenges of fine-grained passive tracking for the low-cost commodity UWB devices, we propose a variance-based temporary-spatial (VATS) mapping algorithm, which relieves the background interference from the perspective of the Bayesian framework. Moreover, a particle filter algorithm has been designed to track the position likelihood changing and to avoid likelihood ambiguity. Experimental results show that the proposed VATS mapping algorithm achieves 50th and 90th percentile errors 0.156 and 0.272 m, respectively, which is promising for practical applications.

High circular polarization ratio (CPR) characteristics were found in permanently shaded regions (PSRs) near the lunar poles. High CPR was regarded as a water ice index. The compact-polarimetric (CP) miniature radio frequency (Mini-RF) radar transmits left-circularly polarized signals and receives horizontally polarized (SHL ) and vertically-polarized (SVL ) echoes from the lunar surface. Statistics of the CPR data show its relations with the relative phase (δ ) between SHL and SVL and the degree of polarization (m) but few interpretations were provided. The average CPR data reach the maximum and minimum at δ =± 90°, respectively. As m becomes very small, the CPR approaches 1. It has been found that CPR is also affected by surface roughness and incidence angle of radar waves. The CPR is now expressed in CP mode to explain the Mini-RF observation. Full-polarimetric radar echoes and CP parameters of the lunar surface are numerically simulated using the bidirectional analytic ray-tracing method. Single-bounce and multiple-bounce scattering components are included in the simulation. Radar images of the lunar crater are simulated with the digital elevation model (DEM) data. The H-α decomposition derived from the full-polarimetric simulation is presented to analyze δ and m. Simulated radar images with different surface roughness are analyzed statistically to study the functional dependences of δ , m, and CPR on incidence angle and roughness. Relationships among δ , m, and CPR are used to analyze the effects of incidence angle, roughness, TiO₂ , and rock abundance on the scattering components. The CPR, m, and δ of PSR craters of different ages are compared with those of nonpolar craters. The results indicate that the CPR, m, and δ are unlikely to be unambiguous evidence of water ice.

Multiple-elevation-beam synthetic aperture radar (SAR) is a concept based on digital beamforming (DBF) in elevation and simultaneous recording of the echoes of multiple transmitted pulses. It enables high-resolution imaging of wide areas and is therefore ideal for the systematic observation of dynamic processes on the Earth's surface. Furthermore, if the pulse repetition interval (PRI) is continuously varied (staggered SAR), it is possible to map a wide continuous swath rather than multiple subswaths separated by ``blind'' ranges. Within the design of multiple-elevation-beam SAR, however, it is fundamental to consider how nadir echoes affect the mapping capabilities of systems with constant PRI and the image quality of staggered SAR systems, where nadir echoes are intrinsically smeared due to the PRI variation. This article addresses the characterization of nadir echoes in multiple-elevation-beam SAR with constant and variable PRI by presenting a parametric model for the nadir echo profile based on real radar measurements, a formulation of the nadir echo location and smearing in staggered SAR, and realistic simulations based on TerraSAR-X data, which show that nadir echo are likely to be barely visible in staggered SAR images. The results of this work are relevant to both the design of future SAR systems and the interpretation of the acquired data.

Snow is an important environmental variable and a primary water resource in many areas of the world. Monitoring seasonal snowpack properties is also crucial for properly managing snow-related hazards such as snow avalanches and snowmelt floods. Recently, an innovative radar architecture, based on the use of two receivers, has been proposed for snowpack monitoring for the case of dry snow, where the snowpack depth and bulk density can be calculated with one single radar measurement, without any kind of external aid. This article presents the extension of this innovative radar architecture for the case of wet snow. The approach to determine, not only the snowpack depth and bulk density but also the liquid water content, is outlined and discussed in detail, along with the experimental validation of the operating principle for two cases., This work was supported in part by the Italian Ministry of Education, University and Scientific Research (MIUR) under Project SIR2014 "SNOWAVE" RBSI148WE5. © 2022, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.

The synergy of active and passive microwave measurements has attracted considerable attention in recent years since they offer complementary information on the characteristics of the observed target (e.g., soil moisture), which motivates the launch of NASA's Soil Moisture Active Passive (SMAP) mission. An assumption of a near-linear relationship between active and passive measurements has been made in the SMAP active-passive baseline algorithm, which is essential to downscale coarse-resolution radiometer brightness temperature (TB) using high-resolution radar backscatter (σ⁰) but has not yet been fully tested under a wide range of ground conditions. Motivated by this, we first examined the validity of the linear assumption by using concurrent and coincident SMAP active and passive observations under diverse environmental factors (e.g., land cover, climate types, terrain and its complexity, soil texture, vegetation coverage, soil moisture, and its dynamics). We also adopted SMAP enhanced TB to evaluate the performance of the disaggregated TB at the same grid resolution of 9 km. The results reveal there is a generally good linear relationship between σ⁰ (no matter in dB or in linear unit) and TB at a global scale. There is no significant difference in the correlation among the four polarization combinations ( $σ ⁰_{hh}$ versus TB $_{h}$ , $σ⁰_{hh}$ versus TB $_{v}$ , $σ⁰_{vv}$ versus TB $_{h}$ , and $σ⁰_{vv}$ versus TB $_{v}$ ) with the $σ⁰_{vv}$ and TB $_{h}$ combination displaying an overall slightly higher correlation. The linear relationship between σ⁰ and TB is significantly affected by environmental factors. Particularly in bare soils and densely vegetated areas (e.g., large forest fraction and vegetation coverage), and arid and polar climate zones, the linear correlation between active and passive measurements worsens, whereas it is favorable in moderate vegetation and soil moisture as well as large soil moisture dynamic conditions. Interestingly, the linear correlation generally decreases as sand content increases while increases with the increase of clay content. The absolute linear correlation coefficient is higher with larger soil moisture dynamics. When compared to SMAP enhanced TB, it shows the linear assumption may have more influence on the correlation (i.e., temporal evolution) of downscaled TB than its absolute accuracy. These findings can enhance the understanding of the geophysical relationship between radar and radiometer signatures, and thus benefit active-passive joint algorithms for future satellite missions.

Synthetic aperture radar raw data simulation (SAR-RDS) is beneficial to the SAR system design, signal processing method verification, and radar parameter optimization. Most SAR-RDS methods are based on the flat terrain assumption. However, the fluctuant terrain in real scene will induce severe SAR beam occlusion effect and produce radar shadow, leading to incorrect RDS results. Thus, a dynamic elevation angle interpolation (DEAI) algorithm is proposed for SAR shadow judgment by considering the actual SAR working process. The key of the proposed DEAI algorithm is the 1-D EAI and shadow visualization update, which avoids the problem that the existing methods cannot judge the shadow of partial areas due to the insufficiently refined mesh grid or the mismatch of the judgment model. Moreover, an evaluation framework named as joint image and signal criteria (JISC) is proposed from the perspectives of SAR imaging and signal processing results to objectively evaluate the SAR-RDS results and solve the problem that the existing evaluation methods cannot be compatible with fluctuant terrain. Finally, the numerical experiment verified our theoretical analyses.