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In this article, an asynchronous information fusion issue is investigated for a camera and a radar in an intelligent driving system. Local camera and radar estimators with missed detections are developed independently at synchronized state update time for target tracking. A Kuhn–Munkers algorithm is used to match local tracking results of camera and radar for fusion estimation of a same target. A fusion estimator is obtained by a matrix-weighted fusion algorithm with wide detection range and reliable fused estimates. Effectiveness of the proposed asynchronous fusion estimator is displayed by experimental results on road vehicle tracking. [ABSTRACT FROM AUTHOR]

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 owing 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 article 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 the motion data simultaneously captured with a stereo video system. Completely substituting the measured by the simulated data for training, a convolutional neural network (CNN) classifier still achieves 80.4% cross-validation accuracy on a challenging gesture set, compared with 89.4% for training on the measured data. Moreover, using the simulated data the classifier is shown to successfully generalize to new scenarios not observed in measurements. [ABSTRACT FROM AUTHOR]

As a noncontact and noninvasive sensor, radar offers attractive modality for human motion recognition in many fields, such as surveillance, smart homes, and assisted living. As a dynamic process, a comprehensive multidomain analysis in stream is crucial for human motion recognition. In this article, a novel spatial–temporal convolution long short-term memory (ST-ConvLSTM) network using dynamic range-Doppler frames (DRDF) based on portable frequency-modulated continuous-wave (FMCW) radar is proposed to address this problem. First, DRDF is introduced to characterize different human motions in time, range, Doppler, and radar cross section (RCS) domains with a time-sequenced range-Doppler maps. Then, ConvLSTM cell is investigated to extract continuous 2-D image features by combining both convolution operation and LSTM cell. Furthermore, a spatial attention module is utilized to emphasize the spatial distribution of human motion in the range-Doppler domain, while a temporal attention module is designed to obtain optimal temporal weights considering behavior continuity. Finally, an extensive radar dataset from 16 volunteers demonstrated its feasibility and superiority in the classification of six typical daily human motions. The contributions of attention modules and its robustness facing individual diversity are also investigated and discussed. [ABSTRACT FROM AUTHOR]

Identity authentication based on Doppler radar respiration sensing is gaining attention as it requires neither contact nor line of sight and does not give rise to privacy concerns associated with video imaging. Prior research demonstrating the recognition of individuals has been limited to isolated single-subject scenarios. When two equidistant subjects are present, identification is more challenging due to the interference of respiration motion patterns in the reflected radar signal. In this research, respiratory signature separation techniques are functionally combined with machine learning (ML) classifiers for reliable subject identity authentication. An improved version of the dynamic segmentation algorithm (peak search and triangulation) was proposed, which can extract distinguishable airflow profile-related features (exhale area, inhale area, inhale/exhale speed, and breathing depth) for medium-scale experiments of 20 different participants to examine the feasibility of extraction of an individual’s respiratory features from a combined mixture of motions for subjects. Independent component analysis with the joint approximation of diagonalization of eigenmatrices (ICA-JADE) algorithm was employed to isolate individual respiratory signatures from combined mixtures of breathing patterns. The extracted hyperfeature sets were then evaluated by integrating two different popular ML classifiers, k-nearest neighbor (KNN) and support vector machine (SVM), for subject authentication. Accuracies of 97.5% for two-subject experiments and 98.33% for single-subject experiments were achieved, which supersedes the performance of prior reported methods. The proposed identity authentication approach has several potential applications, including security/surveillance, the Internet-of-Things (IoT) applications, virtual reality, and health monitoring. [ABSTRACT FROM AUTHOR]

This work provides a proof-of-concept for a linear-position sensor using an ultrawideband (UWB) frequency-modulated continuous wave (FMCW) radar system operating at 126–182 GHz. It is the first work to show environmental compensated and calibration-free distance measurements with micron accuracy at medium range using millimeter-wave (mmWave) radar technology. We addressed hardware imperfections, parameter estimation, and the free-space path, i.e., refractive index and near-field effects. The proposed signal processing chain is robust to interference and of low computational cost. Experiments reveal a systematic error of $\pm 1~\mu \text{m}$ over 4.8 m (0.8–5.6 m), and a random error at a minimum of 30 nm, providing very high sensitivity. [ABSTRACT FROM AUTHOR]

Clock asynchronism is a critical issue in integrating radar sensing into communication networks. It can cause ranging ambiguity and prevent coherent processing of discontinuous measurements in integration with asynchronous transceivers. Should it be resolved, sensing can be efficiently realized in communication networks, requiring few network infrastructure and hardware changes. This article provides a systematic overview of existing and potential new techniques for tackling this fundamental problem. We first review existing solutions, including using a finetuned global reference clock, and single-node-based and network-based techniques. We then examine open problems and research opportunities, offering insights into what may be better realized in each of the three solution areas. [ABSTRACT FROM AUTHOR]

After several decades of continuously optimizing computing systems, the Moore's law is reaching its end. However, there is an increasing demand for fast and efficient processing systems that can handle large streams of data while decreasing system footprints. Neuromorphic computing answers this need by creating decentralized architectures that communicate with binary events over time. Despite its rapid growth in the last few years, novel algorithms are needed that can leverage the potential of this emerging computing paradigm and can stimulate the design of advanced neuromorphic chips. In this work, we propose a time-based spiking neural network that is mathematically equivalent to the Fourier transform. We implemented the network in the neuromorphic chip Loihi and conducted experiments on five different real scenarios with an automotive frequency modulated continuous wave radar. Experimental results validate the algorithm, and we hope they prompt the design of ad hoc neuromorphic chips that can improve the efficiency of state-of-the-art digital signal processors and encourage research on neuromorphic computing for signal processing. [ABSTRACT FROM AUTHOR]

Due to its high resolution and deep penetration depth, microwave ultrawideband radar is a promising tool for the non-destructive testing (NDT) of transportation infrastructure. Microwave radiation can also be used to reconstruct the dielectric properties of objects and therefore can be used to detect an air cavity or metallic rust in concrete. We used contrast source inversion (CSI) as one of the most promising inverse scattering schemes. To resolve the observation domain limitations of NDT, radar imaging method, also known as range points migration (RPM) method, was first incorporated into the inverse scattering algorithm based on CSI as a region of interest (ROI) estimator, which substantially improves the accuracy of complex permittivity reconstruction. In addition, the ROI optimizing scheme based on the CSI cost function is used to enhance ROI accuracy. The effectiveness of the proposed methods is validated via finite-difference time-domain (FDTD)-based numerical simulation, which assumes typical NDT model. [ABSTRACT FROM AUTHOR]

This communication presents a novel systematic design of a high-aperture-efficiency and 2-D beam-scanning nematic liquid-crystal (LC)-based reflectarray (LCRA) that operates in the sixth-generation (6G) midband (7–24 GHz). Despite a 260° phase range, the maximum aperture efficiency is 35.8% at an aperture dimension (F/D) ratio of 0.58, the highest aperture efficiency at the lowest F/D ratio among LCRAs designed to operate on the mmWave band. The proposed LC-based reflectarray unit cell (LC-RUC) has significantly low reflection loss compared to other LC-RUCs. Also, the bias topology of the proposed LC-RUC makes the LCRA capable of 2-D beam scanning. The beam-scanning range of the proposed LCRA is ±50° on the xoz plane and 0°–65° in the yoz plane at 9.55 GHz. A $2 \times 2 $ patch array antenna is designed as the feed antenna to achieve a small F/D ratio system and ease of optimization. When designing the feed antenna, the number of elements or the element spacing is considered to achieve high feed efficiency. In addition, the fabricated planar feed antenna can be easily integrated with a 3-D printed jig in which the focal length can be adjusted for optimization. The lowest side lobe level (SLL) of the proposed LCRA is −15.5 dB. [ABSTRACT FROM AUTHOR]

Conventional radars repeat the transmission of the same waveform after a predefined interval of time called pulse-repetition-interval (PRI). This technique helps estimate the range and Doppler shift of the targets and suppress clutter. However, in dual-function radar communication (DFRC), a different symbol waveform is transmitted after each PRI. Depending on the number of targets, radar receiver output yields several peaks representing different targets’ ranges. Each peak comes with its side-lobes called range-side-lobes (RSL). In DFRC, due to different symbol waveform transmission, peaks and RSLs do not remain coherent, making Doppler shift estimation and clutter suppression challenging tasks. In most of the available literature, iterative receive filters have been designed for DFRC to minimize RSLs and achieve coherent output for different waveforms. However, the proposed receive filter does not guarantee coherent output for more than two waveforms. In contrast, we proposed two novel closed-form algorithms to design receive filters for DFRC that guarantee coherent output response for several waveforms and suppress RSLs. Simulation results demonstrate that the proposed receivers achieve full coherency, and the RSLs are significantly lower than the conventional method. Furthermore, the advantage of achieving coherent output response is shown in target detection and bit-error-rate improvement. [ABSTRACT FROM AUTHOR]

Spectral-compatible radar emission has a paramount importance in realizing the coexistence of radar with wireless communications. In this paper, we deal with the design of spectral-compatible transmit beampattern with minimum peak sidelobe level for a narrowband multiple-input multiple-output(MIMO) radar. We also consider constraints that are imposed due to the practical high power amplifier(HPA) used in modern radars. The constraints are used to control the dynamic range on the magnitude of each signal, to control variations in the transmit power from the individual antennas and the total energy of the signals. The considered problem is challenging as it is non-convex. To this end, we propose an iterative solution that incorporates the majoriztion-minimization(MM) and alternating direction method of multipliers(ADMM) frameworks. Our solution avoids the computationally expensive operations such as matrix inverse and eigenvalue decomposition. We provide numerical results to validate the proposed solution. The results show that the method provides the intended spectral-compatible beampattern while maintaining a beampattern synthesize performance that is comparable to the state-of-the-art work. [ABSTRACT FROM AUTHOR]

Dual-functional radar-communication (DFRC) has been viewed as a promising component in future networks. The considered two-cell interfering DFRC network involves two multi-antenna base stations (BSs), and each BS serves multiple single-antenna users and receives echo signals to detect the target. An optimization framework for the joint transmit beamforming and receive filters design of a coordinated two-cell network is formulated. Specifically, we minimize the transmit power at two BSs subject to the signal-to-interference-and-noise ratio constraints. To solve the formulated non-convex optimization problem, an alternating optimization-based method is invoked. For the transmit beamforming design, a locally optimal successive inner convex approximation (SICA)-based method with fast convergence is firstly proposed. To further reduce the computational complexity, we also provide three zero-forcing (ZF)-based sub-optimal methods for practical consideration. For the receive filters design, a power iterations-based method is proposed. Simulation results validate the effectiveness of our proposed SICA-based locally optimal and ZF-based sub-optimal schemes. [ABSTRACT FROM AUTHOR]

Radar-embedded communication (REC) is a new type of covert communication whereby communication signals are embedded in radar backscattered echoes. Conventional REC waveform design strategies generally involve transforming the radar sampling sequence into a square matrix that can be eigenvalue decomposed; however, it may lose some original characteristics of the radar signal during this process. In this paper, we propose two REC waveform design methods based on singular value decomposition (SVD), namely, SVD-NDP (non-dominant-processing waveform based on SVD) and SVD-SNDP (shaped-non-dominant-processing waveform based on SVD), and derive the similarities between the radar signal and the proposed waveforms. We then simulate the anti-detection performance, anti-interception performance, and communication reliability of the proposed waveforms and analyze the degrees of freedom and computational complexity of their design. The results show that, compared with conventional REC waveforms, the proposed waveforms could improve communication reliability without sacrificing low probability of intercept (LPI) performance and at least double the design degrees of freedom. SVD-NDP and SVD-SNDP algorithms can reduce computational complexity by more than 30% compared with conventional waveform design algorithms based on eigenvalue decomposition when the number of communication waveforms (symbols) is set to 4 (2 bits), and the proportion of the dominant subspace is set to 50%. [ABSTRACT FROM AUTHOR]

A frequency-modulated ultrawideband (FM-UWB) hybrid transceiver, with a high system reuse ratio up to 90%, is fabricated in the 65-nm CMOS process for both short-range wireless communication and high-resolution radar ranging. The radio frequency (RF) front-ends (RFFEs) based on module stacking and current reuse achieve significant RF power savings of about 30% and 50% for the transmitter and the receiver (RX), respectively. The presented IF zero-crossing delay discrimination benefits a high radar resolution less than 1 cm. A multimode relaxation oscillator (OSC) for the reconfigured triangular subcarrier generation and a dual-path ring voltage-controlled oscillator (VCO) for the linear FM, stacked by a wideband push–pull power amplifier (PA), generate an FCC-compliant UWB signal. An active balun embedded low-noise amplifier (LNA) and two symmetric-detuning band-passed filters (BPFs) are stacked with the bandwidth extension to linearly demodulate the UWB FM signal. Experimental results show that the 3.75–4.25-GHz hybrid transceiver has an energy efficiency of 1.9 nJ/bit with an active area of 0.7 mm2 and a power dissipation of 1.9 mW and achieves the RX sensitivity of −71 dBm and the transmitted power of −14.1 dBm, with a bit error rate (BER) of 10−4 at a distance of 4 m under the data rate (DR) of 0.1–1.0 Mbps. The transceiver also achieves the noise figure (NF) of 4.8 dB and the phase noise of −78.6 dBc/Hz at 1-MHz offset frequency. [ABSTRACT FROM AUTHOR]

A high-power Y-junction circulator is proposed for radar applications in the Ku-band (12–18 GHz). The design consists of two identical circulators combined using power splitters at all ports. The overall circulator network achieves 20-dB isolation level and return loss over the Ku-band with a peak power level of 14 kW. An internally matched divider is used at one port of the overall system to eliminate the cavity resonances produced by the practical asymmetries between the two circulators. The asymmetry problem is analyzed in detail to understand the consequences of these practical variations fully. Experimental validation is done by a fabricated prototype and shows a good agreement between the simulated and the measured results with differences in the range of ±2 dB. [ABSTRACT FROM AUTHOR]

Angle of arrival (AoA) for target echo signal detection is crucial in vehicular radar systems, where the estimation of signal parameters via rotational invariance (ESPRIT) provides a high-resolution estimation. A subarray decomposition strategy is presented in this article to create two ESPRIT antenna arrays with enhanced echo signal strengths, applicable to multi-input–multioutput (MIMO) operations for creating a large virtual array. The concept intends to maximize the echo signal’s strength with minimum signal interferences by increasing the aperture sizes of the two ESPRIT antenna arrays. The decomposition produces two virtually overlapped subarrays to increase the subarray aperture sizes in the spatial or spectral representations. It is applied to the MIMO-based arrays for two-way radiation patterns for ESPRIT estimation of AoA. Numerical simulation examples are shown to validate the feasibility and demonstrate the applications. [ABSTRACT FROM AUTHOR]

Fast detection of hazardous objects in millimeter-wave personnel screening can increase the operating efficiency of secure environments. In airports, accurate automatic detection and classification of body-worn objects can reduce the number of pat-downs while keeping the transportation environment safe and secure. Since many benign objects, such as paper and leather, are lossy materials, being able to characterize them and set them aside from the secondary checks will significantly reduce the screening process time. In this article, we introduce an effective image-processing-based method for characterizing lossy materials that might be concealed under clothing at checkpoints. The method has been combined with a modified version of the previously developed algorithm that can be used specifically to characterize lossless materials. The proposed algorithm can automatically distinguish lossless materials from lossy ones and calculate their thickness and permittivities. Starting from the radar reconstructed image showing a cross section of the body, we extract the nominal body contour using the Fourier series, separate body, and object responses, categorize the object as lossy or lossless based on the depression and protrusion of the body contour, and, finally, predict possible values for the object’s permittivity and thickness. Our resulting classification is good, implying fewer nuisance alarms at checkpoints. [ABSTRACT FROM AUTHOR]

This article presents the first demonstration of a full-waveguide feed at W-band, enabling transmit–receive duplexing and 2-D tracking of targets. The proposed device is a compact unit designed to be used as feed of a 94 GHz space-borne radar. Its duplexing concept relies on a septum orthomode transducer polarizer for transmitting and receiving sum signals with opposite circular polarizations. Additionally, the first higher order mode of circular waveguide (TM01) is allowed to propagate inside the device to extract a difference signal for tracking. By comparing received sum and difference signals in amplitude and phase, both angular directions of a target position can be derived. A prototype of the duplexer was fabricated and tested: measurements at 94 GHz show return loss and isolation above 23 dB at all ports, with reasonable performance from 92 to 96 GHz. The measured monopulse characteristic enables 2-D tracking of targets deviated by less than 8.5° from boresight. [ABSTRACT FROM AUTHOR]

In this article, a novel design of compact frequency-selective rasorber exhibiting absorption–transmission–absorption characteristics and having high passband selectivity has been proposed. A square-loop resonator with mounted lossy elements serves as the elemental broadband absorber from 4 to 12 GHz. The transmission frequency at 8.4 GHz is realized by printing a Minkowski fractal-shaped resonator with a high-Q factor on the resistive layer, which provides a transmission pole at the frequency corresponding to the passband of a double-cross-slot-shaped bandpass layer. The functioning of the proposed frequency-selective rasorbers (FSR) is explained by a corresponding equivalent circuit model. The proposed FSR exhibits higher selectivity at the passband, thus making it a suitable candidate for shielding the narrowband radiating system. Measurements performed on the fabricated prototype of a 17 × 17 unit cell array provides experimental validation. Further, a low radar cross-section antenna is realized by integrating a patch antenna with the proposed FSR, which achieves an average out-of-band monostatic radar cross-section (RCS) reduction of 11.92 and 5.04 dB in the lower (4–7.5 GHz) and upper (9.2–10.8 GHz) absorption bands, respectively, while maintaining the other antenna parameters. Furthermore, the bistatic total RCS reduction of 77% and 60% are achieved in the lower and upper frequency bands, respectively. [ABSTRACT FROM AUTHOR]

A significant challenge for dual-beam, codesigned systems, such as for simultaneous radar and communications transmission, has been identified as the spurious beams produced by spatial intermodulation from nonlinearities in the transmitter power amplifier. We demonstrate that tuning the load impedance of the power amplifiers can reverse the elementwise power amplifier nonlinear distortion, reducing the magnitude of the unwanted beam transmissions and restoring the integrity of the dual-beam antenna pattern for application to an active electronically scanned array. A comparison to a recently documented predistortion approach for correcting spurious transmissions is provided, and it is shown that impedance tuning can address both element output power and linearity, whereas predistortion addresses only the linearity issue and causes the amplifier gain in many of the array elements to suffer. For multiple dual-beam angle scenarios, simulation results show that impedance tuning is effective at maximizing beam power in both beam directions, maximizing current gain in the element power amplifiers, and minimizing the size of the unwanted spurious beams. [ABSTRACT FROM AUTHOR]

Multi-input multi-output (MIMO) radar with massive antennas is promising for high resolution applications. However, a big challenge of this system is that the hardware cost and power consumption will increase significantly, if high-resolution quantizers are adopted. In this article, we consider MIMO radar deployed with one-bit digital-to-analog converters, and investigate the problem of designing one-bit transmit sequence with good spatial and spectral properties. Specifically, the one-bit waveform design problem is formulated by minimizing the mean-square error between the desired and designed transmit beampatterns, subject to spectral constraints. The resulting problem, including a nonconvex quartic objective and a nonconvex discrete constraint, is NP-hard, and an alternating optimization (AltOpt) framework with the aid of “almost equivalent” criterion is thereby developed to handle it. Particularly, in the AltOpt framework, a low-complexity algorithm is developed based on the alternating direction method of multipliers approach. Numerical simulations are provided to show the advantages of the proposed method over the state-of-the-art techniques in terms of the spatial and spectral properties as well as computational complexity. [ABSTRACT FROM AUTHOR]

Traditionally, inverse synthetic aperture radar (ISAR) imaging and target tracking are two separate and independent processes. ISAR imaging is usually achieved after data collecting and tracking for a long time, resulting in the problems of low imaging efficiency, information loss, and probing resource allocation difficulty. In this article, we proposed an integration method of tracking and imaging with wideband radar by constructing the relation among signal, data, and image domains, which can realize accurate tracking and high data-rate imaging at the same time. In this integrated imaging and tracking method, a complex-valued reference high-resolution range profile (HRRP) is generated and predicted by exploiting the relation among range-Doppler image, echo in time domain, and target's motion state. Then, a Bayes estimation model is built to extract range phase error between the predicted HRRP and the real-measured HRRP, and the Kalman filter can update the motion state. In addition, in order to increase the efficiency, the decentralized Kalman filter is also introduced to realize the subaperture parallel processing and data fusion in this article. Finally, the sequential motion compensation is carried out to realize accurate motion compensation and sequential imaging. The simulated and real-measured data confirm the proposed algorithm's robust imaging and tracking performance. Experimental results show that the proposed method has excellent efficiency and can simultaneously realize sequential imaging and accurate tracking. [ABSTRACT FROM AUTHOR]

Assume that a modern radar system has a general antenna array configuration consisting of primary channels with high-gain beams and reference channels with low-gain beams. We consider the target detection problem for such array radar systems in Gaussian disturbance with unknown covariance matrix. An adaptive detector is proposed according to the criterion of Wald test. The statistical properties of the proposed detector are provided in the mismatched case, where the nominal target steering vector may not be aligned with the true target steering vector. An analytical expression for the probability of false alarm is derived, which reveals that the proposed detector has a constant false alarm rate property with respect to the disturbance covariance matrix. Moreover, a closed-form expression for the detection probability is obtained in the mismatched case. Simulation results demonstrate that the proposed detector exhibits strong robustness against the target steering vector mismatch. [ABSTRACT FROM AUTHOR]

With the increasing of on-orbit satellites, target dynamic monitoring becomes more and more important in space situation awareness applications. Currently, there are some exploratory methods monitoring attitude-stabilized targets using various high-resolution remote sensing technologies. However, it is still a big challenge to achieve dynamic estimation of spin satellite with single sensor. Inspired by the existing matching based works, this article presents a dynamic estimation method of spin satellite using single-station inverse synthetic aperture radar (ISAR) images. When the angle accumulation is set to be a constant in each ISAR imaging period, the projection change of target structures in the long-term observation sequence is described with the hidden Markov model to build the mathematic expression of target on-orbit state. In this condition, target sequential attitude can be solved with Viterbi decoding algorithm even the azimuth scaling of each image is difficulty due to target spin motion. Then, combined with the radar observation geometry, target sequential attitude parameters are substituted into a spin parameter optimization, which is solved by particle swarm optimization algorithm. In the end, target instantaneous attitude vectors and spin speed are used to express its dynamic during the observation period. Simulation experiments of a typical spin spacecraft, Tiangong-I, confirm the feasibility of the proposed algorithm, and its superiority is also investigated by comparison with the existing work. [ABSTRACT FROM AUTHOR]

One of the few electronic attack techniques that can deceive radars in angle is cross-eye jamming, which mimics the naturally-occurring phenomenon glint. The extreme tolerance requirements of cross-eye jamming mean that a retrodirective implementation is required, but published measurements of cross-eye jamming either ignore the retrodirective implementation or only simulate it. The implementation of a retrodirective cross-eye jammer and its testing against a monopulse radar are described. A procedure for calibrating the jammer is outlined and is shown to be effective by achieving large angular errors. The measured results agree well with the extended analysis of cross-eye jamming and confirm that the implemented jammer is retrodirective. Specifically, the ability of a cross-eye jammer to generate an indicated angle that never becomes zero, thereby potentially breaking a tracking lock, is confirmed. [ABSTRACT FROM AUTHOR]

By using uniformly distributed phases for each bit, one can generate a waveform with an almost ideal aperiodic ambiguity function (thumbtack). Moreover,a set of such codes will potentially exhibit low cross-correlation, making them a family of codes suitable for multiple and diverse applications, ranging from 1) MIMO radars, 2) addressing the joint radar-communication problems, 3) mitigating the interference issues of coexistence of multiple radar systems operating in the same region, and 4) increasing the robustness of the system to jamming. This article presents the full analysis of the probability density function of the peak sidelobe level of such codes, as well as a full treatment of the ambiguity function to show mathematically what could be obtained by generating random phase codes. A simple and effective greedy algorithm for generating multiple codes with improved performance is devised increasing the practicality of this waveform family, and numerical results are provided to support the theoretical ones. [ABSTRACT FROM AUTHOR]

In this article, we develop a new waveform codesign approach for radar–communications spectral coexistence using a decision-theoretic framework called partially observable Markov decision process (POMDP). The POMDP framework’s natural look-ahead feature allows us to trade off short-term for long-term performance, which is necessary in waveform codesign problems with competing objectives and dynamic user needs. As POMDPs are computationally intractable, we extend two approximation methods called nominal belief-state optimization and random-sampling multipath hypothesis propagation to make the codesign approaches tractable. [ABSTRACT FROM AUTHOR]

Target localization, especially the estimation of target altitude, is a challenging task in over-the-horizon radar (OTHR) because of the narrow signal bandwidth as well as the complexity and uncertainty involved in the ionosphere conditions. This task becomes further complicated when the height of the ionosphere layer varies over time. Therefore, it is important to jointly estimate the instantaneous height of the ionosphere and the target altitude as well as other motion parameters. In this article, we achieve these objectives by analyzing the Doppler frequencies of the target local-multipath signals and the clutter. We reveal that the change of the ionosphere height can either enhance or deteriorate the performance of target parameter estimation depending on its direction of motion relative to the target's motion profile. In addition, it is found that the received target and clutter Doppler signatures follow the chirp signal profile at the OTHR receiver. Based on these observations, we develop a general framework that achieves joint target and ionosphere parameter estimation and accounts for the velocity and accelerations of both target and ionosphere layer. Unlike existing time-frequency-based strategies for target localization and tracking in OTHR, where the Doppler signatures only directly determine target vertical velocity and the target altitude is estimated indirectly, the proposed model enables direct estimation of target altitude and ionosphere parameters. The parameter estimation problem in the proposed strategy is analytically derived and the effectiveness is verified using extensive simulation results. [ABSTRACT FROM AUTHOR]

Automatic waveform recognition of overlapping low probability of intercept (LPI) radar signals is an important and challenging task in electronic reconnaissance of the increasingly complicated spectrum environment. In this article, an overlapping LPI waveform recognition processing framework incorporating residual attention-aided U-net generative adversarial network (GAN) and multiinstance multilabel (MIML) classifier is proposed. This framework includes five cascade modules and can achieve satisfactory recognition performance by training with single type of signals only. First, the training signals are transformed into time–frequency images. Then, a residual attention U-net GAN (RAUGAN) with residual learning is employed to reconstruct signal images from noise-contaminated images and with the supervision of the high-quality ones. After that, an instance generation module with asymmetric convolutions generates instance representations, which are then fed into the subsequent residual attention MIML classifier (RAMIML). Finally, an adaptive threshold calibration module is implemented to obtain appropriate thresholds for the final decision. Besides, two loss functions are elaborately designed for the RAUGAN and RAMIML, respectively. Extensive experimental results validate the recognition performance of the proposed framework with a recognition accuracy of 80$\%$ at signal-to-noise ratio $>-18$ dB and show higher robustness on the power ratios and generative performance compared with other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The advantages of sub-terahertz technology (sub-THz, 200–700 GHz) have already been advanced for imaging and recognition of a space object's state from a space-based sensor using inverse synthetic aperture radar (ISAR). The technology benefits from wide absolute signal bandwidths, giving high range resolution and from enhanced sensitivity to surface texture. An experimental validation of such a system in controlled laboratory conditions is presented. Possible image formation methods are proposed and evaluated experimentally. Images of real parts of satellites have been produced at sub-THz frequencies and compared to lower frequency images. Other results include sub-THz bistatic ISAR, and sub-THz cross-polarized images which highlight the scattering from rough surfaces while attenuating the very bright scatterers seen from conventional monostatic images. [ABSTRACT FROM AUTHOR]

Asan important means in low-altitude airspace surveillance, passive radar has been widely studied. With the increasing complexity of the low-altitude environment, the urgent need for radar's capability of automatic target recognition (ATR) emerges. In the field of ATR for passive radar, the method based on radar cross section (RCS) is an important direction for the simplicity of feature extraction. In this article, we exploit the compensated quasi-echo-power (CQEP), i.e., quasi-RCS, to realize ATR in passive radar. We propose an ATR method on the basis of the angular diversity. First, we divide the angular space, which consists of four components of the incident angle and scattering angle of electromagnetic wave, into multiple subspaces. Then, we build a subrecognizer in each angular subspace according to the CQEP distribution characteristics. Each receiving station of the multistatic passive radar recognizes targets in an angular subspace corresponding to its observation and outputs a preliminary decision. Based on the preliminary decisions of all receiving stations, a voting strategy is adopted to make the final decision on the unknown target class in the fusion center. Experimental results based on real-life target data show that the proposed method has a significant improvement on the average correct recognition rate with fusion of three receiving stations, which validates the proposed method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Device-free localization (DFL) enables several new applications in various sectors including smart cities, intelligent transportation, and public safety. DFL relies on a network of sensor radars that transmit, receive, and process reflected signals propagating in a monitored environment. The accuracy of DFL degrades in cluttered environments, due to the presence of undesired objects that reflect the signal. Indeed, the multiple reflections of the signal overlap at the receiver and make the inference of targets' positions challenging. This article presents a theoretical foundation of DFL in cluttered environments by deriving the fundamental limits on DFL accuracy. In particular, we propose a system model that takes into account multiple reflections, nonline-of-sight conditions, and the presence of multiple targets. Building on such a model, we derive the Cramér-Rao bound on the inference accuracy of targets' positions by applying equivalent Fisher information analysis. The proposed bound provides guidelines for the design and analysis of DFL systems operating in cluttered environments. Then, the article presents a case study compliant with the 5G New Radio numerology and channel modeling. Results show how the minimum achievable error is affected by multiple reflections and multiple targets and to which extent the employment of a signal with larger bandwidth and a network with a higher number of receivers can lower the achievable error toward submeter accuracy. [ABSTRACT FROM AUTHOR]

A 24-GHz frequency modulated continuous wave (FMCW) radar system with self-packaged six-port Butler matrix receiver using substrate integrated suspended line (SISL) platform is proposed in this article. Since all active and passive components are integrated on the SISL platform using the standard printed circuit board (PCB) process, the proposed system is highly integrated with low cost. The system is composed of a transmitting (TX) antenna, a Butler matrix with a receiving (RX) antenna array, a single pole four throw (SP4T) switch, a low noise amplifier (LNA), and a six-port receiver. The Butler matrix and SP4T switch are implemented for beam scanning, which has the advantages of low loss and compact size. The SISL-based six-port receiver is designed for quadrature downconversion. The supporting digital signal processing algorithms are also proposed for the calculation and display of multiple targets information. The radar system has shown excellent performance in the measurement of indoor environment, including range, velocity, and direction of arrival (DOA). The proposed radar provides a new solution for a transceiver system. [ABSTRACT FROM AUTHOR]

Range migration (or range focusing) techniques are widely used in optical, acoustic, and microwave real-time image reconstruction methods. They have been successfully applied to far-field 3-D imaging where they rely on plane-wave assumptions, which ignore the data amplitude variation over the acquisition aperture. The accuracy of the plane-wave assumption, however, quickly degrades in close-range imaging, where amplitude variations are significant and where the range to the target is on the order of the range sampling step. Here, we present a range-focusing method of improved accuracy, which is applicable to both far-zone and close-range monostatic radar. It refocuses the system point-spread function (PSF) to any range location, taking into account both magnitude and phase changes. The approach can be applied with any Fourier-based imaging algorithm utilizing the Lippmann–Schwinger equation as the underlying scattering model. Here, it is validated through examples based on simulated and measured data where the images are reconstructed with quantitative microwave holography (QMH). QMH employs measured PSFs to achieve quantitative imaging in real-time. The proposed range-migration method is applicable with measured PSFs, too, leading to reduced system-calibration effort and the ability to focus an image at any desired range. [ABSTRACT FROM AUTHOR]

Compared with a conventional Doppler radar in which target displacement results in phase modulation, target displacement in a self-injection-locked oscillator (SILO)-based radar results in frequency modulation. Since the instantaneous phase is the time integral of frequency, the SILO-based radar is considered to have higher sensitivity than the conventional Doppler radar. However, a direct comparison between the SILO-based radar and the conventional Doppler radar is still needed to quantitatively understand the sensitivity difference. This article provides a rigorous time-domain analysis of the sensitivity of the SILO-based radar with a delay-based frequency demodulator for small-amplitude periodic motions. The analysis follows an approach similar to the time-domain analysis for the conventional Doppler radar. It reveals that two null detection point mechanisms could arise in SILO-based radar systems. The target distance may introduce one null detection point, and the delay added in the frequency demodulator may introduce another. Furthermore, this article also proposes an SILO-based radar with dual null detection points’ removal. Unlike the Doppler radar, where $I/Q$ demodulation eliminates the null detection point introduced by the target distance, $I/Q$ demodulation in the SILO-based radar only eliminates the null detection point introduced by the delay cable. To overcome the other null detection point mechanism, a phase shifter is introduced after the LNA. Experiments were carried out to validate the proposed time-domain analysis and demonstrate that both the techniques need to be used simultaneously to remove both null detection points in the system. The sensitivity comparison was performed using a conventional Doppler radar and an SILO-based radar built with identical microwave components. [ABSTRACT FROM AUTHOR]

A photonics-based leakage cancellation and echo signal de-chirping approach for frequency-modulated continuous-wave radar systems is proposed based on a dual-drive Mach–Zehnder modulator (DD-MZM). The de-chirp reference signal and the leakage cancellation reference signal are combined and applied to the upper arm of the DD-MZM, while the received signal, including the leakage signal and echo signals, is applied to the lower arm of the DD-MZM. When the amplitudes and delays of the leakage cancellation reference signal and the leakage signal are precisely matched, the leakage signal is canceled in the optical domain. The de-chirped signal is obtained after the leakage-free optical signal is detected in a photodetector. An experiment is performed. The cancellation depth of the leakage signal after de-chirping is around 23 dB when the center frequency and bandwidth of the linearly frequency-modulated signal are 11.5 and 2 GHz, respectively. When the leakage cancellation is not employed, the leakage will seriously affect the imaging results and distance measurement accuracy. When the leakage cancellation is enabled, the imaging results of multiple targets can be clearly distinguished, the distance measurement error of a moving target is significantly reduced to less than 10 cm, and a dynamic range increase of 21 dB is achieved. [ABSTRACT FROM AUTHOR]

This is the third of three articles that quantify the high added value of frequent satellite microwave observations of the atmosphere (with a “refresh” time on the order of 1 min) to capture the dynamics of weather systems. Recent advances in small-satellite and microwave miniaturization, such as the “Temporal Experiment for Storms and Tropical systems” (TempEST) millimeter-wave radiometer developed at the Jet Propulsion Laboratory, are paving the way for the design of convoys of spaceborne radars that can directly observe the evolution of severe weather at very fine temporal scales. The analyses presented here are to establish the relation between passive microwave observations and their change in time and the underlying cloud variables and processes and to evaluate the sensitivity to the different physical and instrument parameters. In this third part, simulations are used to demonstrate and quantify the direct sensitivity of a time sequence of mm-wave radiances to the vertical structure of the vertical updrafts in convective storms. It is demonstrated that the brightness temperatures from a pair of low-Earth-orbit (LEO) radiometers maintaining a separation of 1 or 2 min can indeed be used to retrieve the column-maximum magnitude of the vertical wind as well as the height of the maximum. While such passive retrievals do not provide the vertical detail that a pair of radars would produce, the radiometers have a vast swath and therefore enable the observation of an entire storm. The application is therefore quite different from the case of a convoy of radars: rather than compiling radar statistics over multiple years, the radiometer-convoy measurements can be used to analyze every storm that is observed. [ABSTRACT FROM AUTHOR]

An effective filtering technique is required for rainfall rate measurement by weather radar. A Jensen–Shannon distance (JSD)-based thresholding filter is proposed to mitigate nonmeteorological signals, either in clear air or rain situations. This algorithm classifies range-Doppler bins into two classes, hydrometeors and nonhydrometeors, based on spectral polarimetric variable features. The result is a mask to be applied on the spectrograms. The variable selected here is the spectral co-polar correlation coefficient, available in dual-polarization and full polarimetric radars. The algorithm first does global thresholding by finding an optimized threshold value based on the averaged clear-air spectral polarimetric variable distribution. Next, classical filtering steps are carried out like a ground clutter notch filter around 0 ms−1, a mathematical morphology to fill gaps in the hydrometeor areas, and a removal of narrow Doppler power spectra. The second part of this article is the assessment of filtering techniques without ground truth. An assessment without ground truth is useful to select optimal algorithm configurations from a large solution space. Criteria of good filtering are defined both in the spectral and time domain. Based on those criteria, subjective and objective unsupervised evaluation metrics are derived, with a focus on the objective ones. Data, including clear air and rain collected from a full polarimetric Doppler X-band radar in the urban area, are used. With the proposed unsupervised evaluation metrics, the JSD-based thresholding filter is compared to two spectral polarimetric filters. Overall, the JSD-based filter performs very well considering both the subjective and the objective evaluation metrics. [ABSTRACT FROM AUTHOR]

Radar sounders (RSs) are gaining importance in planetary missions thanks to their unique capability of providing direct measurements of subsurface (SS) structures. To support their design and data interpretation, several electromagnetic (e.m.) simulation techniques have been developed with enhanced capabilities for emulating the RS acquisition process. However, the raw simulated radargrams obtained from e.m. simulators are difficult to interpret and analyze without a focusing operation, which results in an underestimation of the RS detection performance. While frequency methods for range and azimuth compression of real RS data are well-established, their use on simulated data is not addressed in the literature and requires major modifications. This article presents a novel method that implements azimuth compression using unfocused and focused processing on simulated raw data. The proposed method is based on an adaptation of the range-Doppler algorithm to the case of raw data generated by a coherent RS simulator. The method is demonstrated in three case studies to show the similarity between simulated and real data processing: 1) simple geometries; 2) a simulated SHAllow RADar (SHARAD) radargram compared with the real data product; and 3) a real application scenario for supporting the design of a new RS instrument. The results indicate higher fidelity of the focused simulated data with the real data product and the target structure, confirming the usefulness of the proposed approach in obtaining realistic processing of simulated radargrams. [ABSTRACT FROM AUTHOR]

A small-aperture receiving array occupying a small area provides convenience for the layout of high-frequency (HF) radars. However, this kind of antennas has a wide beam, which adversely affects the wave measurements. To solve this problem, a method for extracting wave parameters from wide-beam radar echoes, which models current variations across the beam, is proposed in this article. The nondirectional wave spectrum is extracted from the echoes of a small-aperture HF radar, and wave parameters such as the significant wave height, peak, and mean wave period are then calculated from it. Simulation is carried out to assess the performance of the method for different current velocities, radar frequencies, and wind conditions. The proposed method is then applied to a nine-day dataset collected by a multifrequency HF radar with a circular receiving array (MHF-C) radar for further validation via comparisons between the radar-estimated and the buoy-measured wave parameters. Some factors that may affect the performance of wave height measurements are analyzed, such as the signal-to-noise ratio and radial current velocity. The correlation coefficient (CC) between the radar-estimated and the buoy-measured significant wave height is 0.90, and the root mean square difference (RMSD) is 0.51 m. For the mean wave period, the CC is 0.61 and the RMSD is 0.67 s. The results demonstrate that the significant wave height and the mean wave period extracted by the proposed method are consistent with the buoy-measured values, and the proposed method can overcome the broadening influence of the Doppler spectrum caused by ocean currents. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel processing algorithm for frequency-modulated continuous-wave (FMCW) ice sounding radar, which addresses the along-track focusing of internal reflecting horizons. It is a modified frequency scaling algorithm that can handle the two-layer medium imaging model as well as the Doppler impact of the motion within the sweep in a nadir-looking radar. The proposed algorithm’s comprehensive derivation and implementation processes are described. In the range-Doppler domain, a really effective formulation for radar signals is also presented, which considers refraction effects and electromagnetic wave propagation velocity changes at the interface of two different media. Point target simulations are carried out to demonstrate the algorithm’s performance. The proposed method is also tested on the real data acquired by the shallow-layer-detection ice sounding radar (SLDISR). The result shows the applicability of the proposed method for imaging the ice sheet. [ABSTRACT FROM AUTHOR]

Spaceborne radar sounders are high frequency (HF)/very high frequency (VHF) nadir-looking sensors devoted to subsurface investigations. Their data interpretation can be severely hindered by off-nadir surface clutter. Recent literature showed that the clutter suppression capabilities of this class of systems can be greatly enhanced by deploying an array of orbiting sensors in formation flight synthesizing a narrow radar antenna beam. In this article, we assess the capability of distributed radar sounding to discriminate clutter from subsurface returns by exploiting direction of arrival (DOA) estimation techniques. This is achieved by first outlining an approach for designing and evaluating the distributed radar sounder DOA estimation performance as function of the radar system parameters (e.g., intersensor distance) and external noise factors such as ionospheric scintillations. Then, the theory is complemented by radar simulations of several acquisitions over Greenland assuming a variety of subsurface geometries. The simulations confirm that clutter discrimination through DOA estimation is a viable approach to further improve the array capability in disambiguation of subsurface echoes from surface ones. [ABSTRACT FROM AUTHOR]

In recent years, gait-based person identification has gained significant interest for a variety of applications, including security systems and public security forensics. Meanwhile, this task is faced with the challenge of disguised gaits. When a human subject changes what he or she is wearing or carrying, it becomes challenging to reliably identify the subject’s identity using gait data. In this paper, we propose an unsupervised domain adaptation (UDA) model, named Guided Subspace Alignment under the Class-aware condition (G-SAC), to recognize human subjects based on their disguised gait data by fully exploiting the intrinsic information in gait biometrics. To accomplish this, we employ neighbourhood component analysis (NCA) to create an intrinsic feature subspace from which we can obtain similarities between normal and disguised gaits. With the aid of a proposed constraint for adaptive class-aware alignment, the class-level discriminative feature representation can be learned guided by this subspace. Our experimental results on a measured micro-Doppler radar dataset demonstrate the effectiveness of our approach. The comparison results with several state-of-the-art methods indicate that our work provides a promising domain adaptation solution for the concerned problem, even in cases where the disguised pattern differs significantly from the normal gaits. Additionally, we extend our approach to more complex multi-target domain adaptation (MTDA) challenge and video-based gait recognition tasks, the superior results demonstrate that the proposed model has a great deal of potential for tackling increasingly difficult problems. [ABSTRACT FROM AUTHOR]

In recent years, there are increasing interests and applications on radar–communication integration for system miniaturization, cost reduction, and so on. Moreover, thanks to the common functions of hardware components including transceiver, antennas, and even basic signal/data processing, the integrated design of radar and communication systems becomes feasible. In this article, through design of proper time sequences, waveforms, and recognition algorithms, radar sensing and wireless communication can be integrated into 4-D antenna arrays simultaneously. In addition, with the high design degrees of freedom of 4-D arrays, the proposed approach can also provide a low probability of intercept capability. Selected numerical and experimental results are provided to validate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

High-performance computing-based electromagnetic (EM) emulators are used to simulate real-time complex EM wave interactions between multiple radar targets, transmitters, and receivers. The radar cross section (RCS) of the radar targets are required to be stored as a table; however, the needed storage size increases dramatically with the angle and frequency sampling density. In this article, we present an innovative approach of constructing a concise spherical harmonic-based anisotropic point scatterer model that the emulators can use as part of the computations. The point scatterer model is constructed directly from the precomputed RCS data. First, we use only the monostatic RCS data and compute the spherical harmonic-based monostatic point scatterer model by solving a linear least-squares problem which has a group sparsity constraint. Then, we further compute the spherical harmonic-based bistatic point scatterer model using the full bistatic RCS data. The problem is formulated as a bilinear least-squares problem. The problem is solved using the normalized iterative algorithm, which linearly solves two parameters in a back and forth manner. The results show that the point scatterer model can effectively represent the bistatic RCS data of a radar target. [ABSTRACT FROM AUTHOR]

Due to the asymmetry of the elements’ position distribution and polarization direction, it is a challenge to synthesize difference patterns with large slope and symmetric main-lobe on 3-D conformal beam-scanning arrays with asymmetric radiation aperture. In this article, an approach to synthesize the optimal difference patterns for 3-D conformal arrays with asymmetric radiation aperture is proposed. To determine the limitation region of the main-lobe and sidelobe for a 3-D conformal array, an initial difference pattern is generated by the joint multidimensional vector clustering method. Then, an auxiliary phase function is introduced to convert the nonconvex constraint of the symmetry of the difference beam into a convex one. Finally, an iterative convex optimization is applied to obtain the optimal difference pattern. The optimization progress is finished by extracting the vector field patterns of a simulated antenna element. Two design examples employing hemispherical conformal array (HCA) and conical conformal array (CCA) with asymmetric radiation aperture are implemented to demonstrate the effectiveness of the proposed method. Difference patterns with −20 dB sidelobe level (SLL) and large slope are obtained in both numerical and simulated results of the two design examples. [ABSTRACT FROM AUTHOR]

Being a key technology for beyond fifth-generation wireless systems, joint communication and radar sensing (JCAS) utilizes the reflections of communication signals to detect foreign objects and deliver situational awareness. A cellular-connected unmanned aerial vehicle (UAV) is uniquely suited to form a mobile bistatic synthetic aperture radar (SAR) with its serving base station (BS) to sense over large areas with superb sensing resolutions at no additional requirement of spectrum. This paper designs this novel BS-UAV bistatic SAR platform, and optimizes the flight path of the UAV to minimize its propulsion energy and guarantee the required sensing resolutions on a series of interesting landmarks. A new trajectory planning algorithm is developed to convexify the propulsion energy and resolution requirements by using successive convex approximation and block coordinate descent. Effective trajectories are obtained with a polynomial complexity. Extensive simulations reveal that the proposed trajectory planning algorithm outperforms significantly its alternative that minimizes the flight distance of cellular-aided sensing missions in terms of energy efficiency and effective consumption fluctuation. The energy saving offered by the proposed algorithm can be as significant as 55%. [ABSTRACT FROM AUTHOR]

The roll-out of various emerging wireless services has triggered the need for the sixth-generation (6G) wireless networks to provide functions of target sensing, intelligent computing and information communication over the same radio spectrum. In this paper, we provide a unified framework integrating sensing, computing, and communication to optimize limited system resource for 6G wireless networks. In particular, two typical joint beamforming design algorithms are derived based on multi-objective optimization problems (MOOP) with the goals of the weighted overall performance maximization and the total transmit power minimization, respectively. Extensive simulation results validate the effectiveness of the proposed algorithms. Moreover, the impacts of key system parameters are revealed to provide useful insights for the design of integrated sensing, computing, and communication (ISCC). [ABSTRACT FROM AUTHOR]

We present an approach to automatically generate semantic labels for real recordings of automotive range-Doppler (RD) radar spectra. Such labels are required when training a neural network for object recognition from radar data. The automatic labeling approach rests on the simultaneous recording of camera and lidar data in addition to the radar spectrum. By warping radar spectra into the camera image, state-of-the-art object recognition algorithms can be applied to label relevant objects, such as cars, in the camera image. The warping operation is designed to be fully differentiable, which allows backpropagating the gradient computed on the camera image through the warping operation to the neural network operating on the radar data. As the warping operation relies on accurate scene flow estimation, we further propose a novel scene flow estimation algorithm which exploits information from camera, lidar and radar sensors. The proposed scene flow estimation approach is compared against a state-of-the-art scene flow algorithm, and it outperforms it by approximately 30% w.r.t. mean average error. The feasibility of the overall framework for automatic label generation for RD spectra is verified by evaluating the performance of neural networks trained with the proposed framework for Direction-of-Arrival estimation. [ABSTRACT FROM AUTHOR]