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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]

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]

When a missile-borne radar system works in downward-looking surveillance mode, the broadened ground clutter signal in virtue of platform high-speed motion will be received by the radar receiver, which will cause difficulty in moving target detection and attacking. Unlike airborne and spaceborne platforms, a missile-borne platform exhibits some unique motion characteristics, such as diving, spinning, and coning, causing the clutter space–time distribution property significantly different from those of airborne and spaceborne radar platforms. In addition, the forward target striking requirements make the missile-borne clutter space–time spectrum further exhibit the severe range-dependent property. To deal with these issues, accurate motion modeling of a missile-borne radar platform is first carried out in this article, where the complex platform motions including forward-looking diving, spinning, and coning are considered. Then, the autocorrelation processing combined with iterative adaptive approach is applied to estimate the clutter angle-Doppler center frequencies, so as to effectively realize the clutter nonstationary compensation along spatial and temporal directions. Finally, a time-domain sliding window-based subspace projection method is proposed to achieve the robust clutter suppression. Both simulation and real-measured radar data processing results are presented to validate the effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

During the observation of micromotion targets in space, inverse synthetic aperture radar usually obtains the narrowband and wideband echoes simultaneously. In order to exploit their rich information in target electromagnetic scattering, shape, structure, and motion, this article proposes a recognition method of space micromotion targets based on decision fusion. The proposed method extracts physical features from the radar cross section and the joint time–frequency distribution from narrowband echoes, while extracts the data features from high-resolution range profiles and range-instantaneous-Doppler image by convolution neural network. Finally, particle swarm optimization is adopted to decision-level fusion so as to realize high-precision recognition. The recognition results of electromagnetic simulated data under various conditions have demonstrated the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

RF sensors have been recently proposed as a new modality for sign language processing technology. They are noncontact, effective in the dark, and acquire a direct measurement of signing kinematic via exploitation of the micro-Doppler effect. First, this work provides an in depth comparative examination of the kinematic properties of signing as measured by RF sensors for both fluent ASL users and hearing imitation signers. Second, as ASL recognition techniques utilizing deep learning requires a large amount of training data, this work examines the effect of signing kinematics and subject fluency on adversarial learning techniques for data synthesis. The following two different approaches for the synthetic training data generation are proposed: 1) adversarial domain adaptation to minimize the differences between imitation signing and fluent signing data and 2) kinematically-constrained generative adversarial networks for accurate synthesis of RF signing signatures. The results show that the kinematic discrepancies between imitation signing and fluent signing are so significant that training on data directly synthesized from fluent RF signers offers greater performance (93% top-5 accuracy) than that produced by adaptation of imitation signing (88% top-5 accuracy) when classifying 100 ASL signs. [ABSTRACT FROM AUTHOR]

In this article, we define an ambiguity function (AF) for the generalized wideband multiple-input multiple-output (MIMO) radar, wherein the AF combines the signal processing in the fractional Fourier domain with all the functions of conventional AFs. We name it as the fractional AF for the wideband MIMO radar. In order to obtain the AF, we start from introducing the fractional order that relates to fractional signal processing into the matched-filter exploited by the AF, based on which we then derive the explicit expression of the AF. We provide explanations and implications of the fractional AF, and also derive its simplifications in terms of the case of slow-moving targets in far field. Moreover, we derive corresponding properties for the fractional AF, and meanwhile, we conduct analysis on the computational complexity of the AF. On the basis of the AF definition as well as its simplifications, we establish relationships of our proposed fractional AF to conventional AF forms. We show that our defined fractional AF can serve as a generalized AF form since conventional AFs are special cases of it. Our simulations show that the proper selection of fractional-orders can enable low sidelobe levels of the fractional AF for wideband MIMO radar. [ABSTRACT FROM AUTHOR]

A dual-polarized radar system is utilized for non-contact sensing applications involving rotational motion. Polarization-centric methods are employed to sense and characterize responses from an electric motor with various bearing faults and to sense responses from a high-velocity fan. Conventional characterizations, such as power spectral densities and micro-Doppler responses, are compared with polarization-based statistical approaches such as polarization entropy and a newly proposed micro-Entropy approach inspired by the micro-Doppler approach. [ABSTRACT FROM AUTHOR]

Doppler ambiguity in the range-Doppler domain of linear frequency modulated (LFM) continuous wave radars occurs when a target’s Doppler frequency exceeds half of the chirp repetition frequency. Doppler ambiguity is common in a variety of civil and military radar applications, and an extension of the maximal unambiguous Doppler shift is critical for their practical use. This article utilizes previously neglected high-order phase terms in the received LFM radar echo for extension of maximum unambiguous velocity. A computationally feasible velocity estimation algorithm using hypotheses testing with local maximum likelihood is derived. The ability of the proposed low-complexity algorithm to estimate previously ambiguous target velocity is investigated using recorded automotive radar measurements and via simulations. The performance of the proposed algorithm is evaluated using a novel model of the Doppler estimation errors that accounts for Doppler ambiguity. The ability of the derived model to predict the threshold phenomenon is demonstrated via simulations. [ABSTRACT FROM AUTHOR]

In this article, we propose a new signal-decomposition algorithm composed of three steps: principal components analysis to yield high-resolution range profiles with improved signal-to-noise ratio; estimation of whitening and mixing matrices using independent component analysis in distributed radar network; and signal decomposition to obtain inverse synthetic aperture radar (ISAR) images that correspond to rigid body and fast-rotating parts by using estimated two matrices regardless of complicated range migration. The proposed method efficiently removes image blur caused by micro-Doppler (MD) signals of rotating parts and reduces the sensitivity to noise. In simulations, our proposed method could perform accurate and robust removal of the MD signatures to obtain a focused ISAR image of an aircraft with fast-rotating parts. [ABSTRACT FROM AUTHOR]

Range/Doppler migration and velocity ambiguity are two well-known problems encountered in high-speed moving target detection using a linear-frequency-modulated continuous-wave 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 full velocity resolutions, as well as full coherent integration gains. It attains a computational complexity comparable to that of the conventional 2-D-FFT-based range–Doppler processing 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. The effectiveness and the computational efficiency of the proposed algorithm are demonstrated by numerical examples. [ABSTRACT FROM AUTHOR]

Detection and tracking of small targets in sea clutter using high-resolution radar is a challenging problem. Recently, a Bernoulli track-before-detect (TBD) filter has been developed for an airborne scanning radar in the maritime domain, with the purpose of detection and tracking of short-exposure targets by using a fast scanning mode (i.e., short dwell-time and noncoherent integration). This article investigates the potential benefits of coherent radar processing and exploitation of Doppler information in TBD, when the radar operates in a slower scanning mode (i.e., using longer dwell times). For this purpose, a new Bernoulli TBD filter is developed, which is capable of processing full three-dimensional (range-azimuth-Doppler) radar data. The amplitude of sea clutter is modeled using the K distribution with Doppler-dependent shape and scale parameters. Numerical results indicate that the new Bernoulli TBD outperforms the fast scanning TBD filter, at signal-to-interference ratios below 6 dB. [ABSTRACT FROM AUTHOR]

This article introduces a new class of Doppler-tolerant and estimation-capable radar waveforms called logarithmic frequency waveforms (LFWs). These waveforms are created by mapping the magnitudes, phases, and spacing of good digital radar codes onto a set of carriers defined over a logarithmically warped frequency axis. This mapping preserves the digital code's desirable autocorrelation mainlobe-to-sidelobe ratio when matched filtering is done over the warped frequency variable. The logarithm converts the multiplicative Doppler shift into an additive translation of the code's autocorrelation; thus, the location of the matched filter output's maximum is used to estimate the waveform's Doppler shift. This applies even if the code is neither inherently Doppler tolerant nor Doppler detection capable. We introduce two major classes of LFWs, logarithmic frequency codes, and logarithmic frequency rulers. We numerically illustrate their ambiguity functions and compare their Doppler estimation performance in additive white Gaussian noise against the linear chirp (linear frequency modulated) outfitted with the extended matched filter and the hyperbolic-frequency-modulated waveform. [ABSTRACT FROM AUTHOR]

The Doppler dilemma, an inherent dichotomy between range and velocity estimation in pulse-Doppler radars, has been the subject of many works in literature. Classical approaches for solving its intrinsic ambiguities usually rely on the subdivision of the coherent processing interval into multiple bursts of different pulse repetition frequency (PRF). Besides some additional complexity related to the PRF selection and the extraction of the unambiguous measurements, these techniques reduce the coherent gain, introducing losses that, in some cases, can be in the order of several decibels. Within this context, this article presents a novel velocity estimation scheme, based on a subpulse processing architecture and random waveforms. It is shown that, with the proper selection of system parameters, the subpulse-to-subpulse phase shift can be evaluated and used to extend the unambiguous measurements as far as needed. The algorithm performance has been evaluated through statistical simulations, and its complexity addressed with a real-time implementation. The proposed architecture was also verified considering different noise waveforms, including sidelobe optimized ones. The results have shown that, besides extending the unambiguous measurements, and improving the Doppler tolerance, the subpulse processing has also increased the system robustness to the Doppler mismatch effects, reducing sidelobes, and thus, extending its applicability. [ABSTRACT FROM AUTHOR]

In this article, an algebraic solution for localizing a moving target using a nonstationary multistatic radar system is proposed. By utilizing the quadruple hybrid measurement set, which consists of time delay, Doppler shift, angle of arrival, and angle rate measurements, the proposed method can estimate the target position and velocity vectors via a simple one-stage weighted least squares estimator without the need for introduction of the nuisance parameters, which enables us to locate the target with the minimum number of antennas. The proposed estimator takes the uncertainty concerned with the position and velocity of the antennas in its design. The proposed estimator is shown to be approximately unbiased and efficient under small Gaussian noise level assumption, that is, the estimator achieves the smallest possible variance (the Cramér–Rao lower bound) among all other unbiased estimators. Numerical simulations demonstrate substantial performance improvement of the proposed estimator over the state-of-the-art methods presented for moving target localization. [ABSTRACT FROM AUTHOR]

In multitarget scenarios, the masking of small targets by large targets nearby may severely deteriorate radar detectability due to the range and Doppler sidelobes. In this article, a 2-D joint iterative adaptive filtering (2-D JIAF) method is proposed, by adopting the reiterative minimum mean square error (RMMSE) criterion to the outputs of a 2-D matched filter. The main advantages of the proposed method over the state-of-the-art (SOTA) methods, including modified adaptive multipulse compression and iterative adaptive approach, are twofold: 1) it is able to suppress the sidelobes in both range and Doppler dimensions and thus obtain an improved range-Doppler image; 2) the computational complexity is significantly reduced by adopting a small processing window in both range and Doppler dimensions. The derivation of 2-D JIAF is detailed and an efficient two-stage implementation is outlined. The performance of 2-D JIAF is validated with simulation results over a wide range of scenarios and compared with two SOTA approaches. The impacts of different parameters, including the number of iterations and the choice of the size of the processing window, are also extensively studied with Monte Carlo trials. [ABSTRACT FROM AUTHOR]

Time reversal can resolve multipath problems and increase the detection probability, but the detection performance decreases when the target is moving. Because of the change in the channel response due to target motion, the focusing effect of a time-reversal-transmitted signal is reduced. In this article, a novel method based on time reversal, which detects a moving target embedded in a multipath environment with channel variation, is proposed. We establish conventional and time-reversal signal models of a moving target in an indoor diffuse multipath environment and derive likelihood ratio tests under these two conditions. The channel parameters and the changes due to target motion are obtained by echo estimation and are exploited as useful information by the detectors. The channel changes are taken into account in the time-reversal detector to improve its robustness. The time-reversal detector proposed in this article possesses the constant-false-alarm-rate property with respect to the unknown background noise. Although Monte Carlo simulation analysis has illustrated the superior performance of both conventional and time-reversal detectors and proved that both methods can improve the detection probability by exploiting the multipath effect, the time-reversal method outperforms the conventional method due to the spatial and temporal focusing effect on the channel. [ABSTRACT FROM AUTHOR]

In this article, we review and compare different methods for the localization of an illuminator of opportunity for passive radar systems employing cooperative targets. For assessment and comparison, we use numerical simulations and real-world radar measurements. To achieve reliable operation under real-world conditions, a correct and robust association of the bistatic radar target observations with ground truth information is necessary. We introduce a novel solution to this issue with an efficient preprocessing algorithm based on a planar approximation. [ABSTRACT FROM AUTHOR]

A multiple-input multiple-output (MIMO) radarwith widely separated antennas on moving platforms suffers from the effects of platform deviations on the target parameter estimation since the trajectories of the moving platforms are sensitive to environmental factors, such as strong wind. This article addresses the joint estimation of multiple target positions and velocities as well as radar system deviations to minimize the impact of platform deviations. The proposed algorithm can also be regarded as a self-calibration technique. First, the grid search dimensions for parameter estimation are reduced via a generalized maximum likelihood (GML) algorithm. Second, the adaptive gradient (AdaGrad) method is used to implement the GML estimation for multitarget echo delays and Doppler shifts. Finally, to address the nonlinear estimation problem of interest, the iterative least squares method is used to estimate the multiple target positions and velocities as well as radar system deviations based on the estimated delays and Doppler shifts. Prior information, such as target positions or the probability distribution of the echo coefficient, is not needed in the proposed method. The parameter identifiability is also derived in this article. Numerical simulations show that compared to a method without the estimation of system deviations, the proposed method is more efficient with respect to the derived Cramér–Rao bound. [ABSTRACT FROM AUTHOR]

This article addresses the problem of clutter cancelation for slowly moving target detection and localization in multichannel passive radar onboard mobile platforms. A post-Doppler space-time adaptive processing (STAP) approach is exploited in the case of an angle-dependent imbalance affecting the receiving channels. While the clutter suppression capability is ensured by the adaptivity of space-time filtering, different solutions are compared, aimed at recovering the detection performance losses associated with channel calibration errors. A space-time generalized-likelihood ratio test (GLRT) scheme is considered, where the steering vector is not specified in the spatial domain, resulting in a noncoherent integration of target echoes across the receiving channels. This is compared with a fully coherent GLRT scheme where echoes from the stationary scene are exploited for the proper calibration of spatial steering vector mismatch. The first scheme proves to be a simple solution for target detection in the passive radar case, offering comparable clutter cancelation capability. The second scheme, at the expense of an additional stage, offers slightly better detection performance and preserves target direction-of-arrival (DoA) estimation capability. Finally, the STAP scheme is employed for the maximum-likelihood estimation of target DoA, evaluating the role of the steering vector calibration against the negative impact of channel imbalance. The effectiveness of the proposed approaches is tested against both simulated and experimental data from a DVB-T-based mobile passive radar. [ABSTRACT FROM AUTHOR]

Through-wall human sensing is of high interest for both military and nonmilitary applications, including counter-terrorism and law enforcement purposes, particularly in the modern, highly urbanized environment. Conventional active radar sensors possess good performance, however, at the expense of high cost and complexity of the transmitter/receiver design. This article demonstrates the effectiveness of a passive through-wall human sensing technique using opportunistic WiFi signals. With a simple software-defined radio receiver and advanced signal processing techniques, the position of indoor WiFi access point can be accurately localized, and its signal can be exploited to clearly detect the Doppler/micro-Doppler of human motions inside the room. Compared to the results in the current literature, this article demonstrates better detection sensitivity and capability to sense not only major motions such as walking and waving hand, but also very small human motions such as keyboard typing and breathing. In addition, an iterative adaptive approach is applied to effectively improve the Doppler resolution of WiFi passive radar. These enhanced sensitivities greatly expand the potential of WiFi passive radar for through-wall sensing applications. [ABSTRACT FROM AUTHOR]

This article addresses the coherent integration problem for detecting a highly maneuvering radar target with the range migration (RM) and Doppler frequency migration (DFM). Although many research efforts have been devoted toward this problem, how to strike a good balance between the detection performance and the computational complexity is still a challenge yet. In the algorithm, proposed in this article, a neural network is first developed to directly infer the target trajectory from the radar echo, and then the target energy distributed along the inferred trajectory is accumulated via the dechirp technique for detection. Since the proposed algorithm corrects the RM and compensates the DFM via the data-driven and model-driven approaches, respectively, we argue that the proposed algorithm operates in a model-and-data-driven approach. Besides, we fully integrate the domain knowledge into the development of the neural network, and simulation results suggest that this practice helps improve the detection performance of the proposed algorithm. Finally, numerical experiments are provided to show the high detection performance and computational efficiency of the proposed algorithm. Furthermore, we visualize the learned information of the neural network and find that it accords with our domain knowledge, demonstrating the rationality of the neural network's predictions. [ABSTRACT FROM AUTHOR]

In this article, we propose a novel method utilizing iterative semidefinite relaxation for geolocation of stationary uncooperative radars. In our scenario, the geolocation is to be performed in a receiver located on a moving platform. The proposed method uses frequency measurements that are Doppler-shifted due to the platform motion. First, constructed nonconvex maximum likelihood cost function for position estimation is relaxed to a convex optimization problem by applying linearization to range variables. Then, at each iteration of the method, carrier frequency and position of the radar are estimated jointly. Conducted experiments show that a few iterations are enough for convergence to accurate estimates. The proposed method is computationally less expensive compared to traditional techniques, which require extensive grid search procedures in either position or carrier frequency parameter space. In the experiments, the performance of the proposed method is compared to the state-of-the-art techniques and the Cramer–Rao lower bound (CRLB). It is observed that the proposed method attains the CRLB at low noise levels while still providing accurate solutions at high noise cases. Furthermore, it is also seen that platform-radar geometry has an impact on the proposed method's performance. If the radar lies in the convex hull of the receiver path, the proposed method performs significantly better due to improvement in the linearization of range values. [ABSTRACT FROM AUTHOR]

Randomized stepped-frequency (RSF) radar, which transmits random-frequency pulses in a coherent processing interval (CPI), has an excellent electronic counter-countermeasures (ECCM) performance and the ability to synthesize wide-frequency band with a narrow bandwidth receiver. However, due to the use of different frequency pulses, RSF waveform is incompatible with the conventional moving-target-detection (MTD) technique, which makes clutter suppression a difficult problem for RSF radar and limits its application. In this article, the effect of clutter on the coherent processing for RSF radar is first analyzed. The result shows that coherent processing can improve the signal-to-clutter ratio on target Doppler channel by $N$ (number of pulses in one CPI) times, which suppresses weak clutter scatterers to a large extent whilst strong clutter scatterers would still be left influential. Focusing on dominant clutter scatterers, the adaptive range-Doppler clutter suppression algorithm, which is based on designing clutter suppression filters with two-dimensional property to obtain the clear high-range-resolution profile of moving target in clutter environment, is then proposed for RSF radar. The proposed algorithm, which takes into account clutter Doppler extension, can be used for RSF radar coherent processing in clutter environment. [ABSTRACT FROM AUTHOR]

In this article, an unmanned aerial vehicles detection system is proposed for an X-band ground-based surveillance frequency modulated continuous wave Doppler radar. Two novel features are directly extracted from the Doppler processing results without a time-frequency analysis. Experimental results on measured radar echo signals show that our system consistently outperforms the state of the art in terms of detection accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

Various correlation-based receivers have been proposed in passive bistatic and active monostatic radar exploiting orthogonal frequency-division multiplexing communications signals, but too little has been dedicated to establishing their relations and advantages over each other. Accordingly, this article provides an analytical comparison of the common filters in such waveform sharing scenarios, along with a performance analysis regarding three criteria: computational complexity, signal-to-interference-plus-noise-ratio, and resilience to ground clutter. The last two especially assess the possible detrimental effects of the random sidelobes (or pedestal) induced by the data symbols in the range-Doppler map. Although simulations show that none of the filters performs unanimously better, the ones employing circular correlations globally evidence attractive results. [ABSTRACT FROM AUTHOR]

We consider the design of sets of discrete-phase, including binary/quaternary, sequences for phase-modulated continuous-wave multiple-input multiple-output radar in the presence of nonnegligible Doppler shift. We consider the peak sidelobes of auto- and cross-correlations in a desired interval of the Doppler shift as the performance metric of the design. Then, the design problem is formulated via imposing the discrete-phase constraint for each element of the sequences, with emphasis on binary as well as quaternary cases. This problem is nonconvex and hence hard to solve. We introduce a method based on the block coordinate descent framework to solve the optimization problem. We also modify the proposed method to efficiently update the subproblem associated with each iteration. Also, we extend it to account for only a low-correlation zone in the presence of Doppler shift. Numerical examples are provided to illustrate the effectiveness and performance of the proposed algorithm in comparison with the existing methods. [ABSTRACT FROM AUTHOR]

Deep neural networks have recently received a great deal of attention in applications requiring classification of radar returns, including radar-based human activity recognition for security, smart homes, assisted living, and biomedicine. However, acquiring a sufficiently large training dataset remains a daunting task due to the high human costs and resources required for radar data collection. In this article, an extended approach to adversarial learning is proposed for generation of synthetic radar micro-Doppler signatures that are well adapted to different environments. The synthetic data are evaluated using visual interpretation, analysis of kinematic consistency, data diversity, dimensions of the latent space, and saliency maps. A principle-component analysis-based kinematic-sifting algorithm is introduced to ensure that synthetic signatures are consistent with physically possible human motions. The synthetic dataset is used to train a 19-layer deep convolutional neural network to classify micro-Doppler signatures acquired from an environment different from that of the dataset supplied to the adversarial network. An overall accuracy of 93% is achieved on a dataset that contains multiple aspect angles (0$^{\circ }$, 30$^{\circ }$, and 45$^{\circ }$ as well as 60$^{\circ }$), with 9% improvement as a result of kinematic sifting. [ABSTRACT FROM AUTHOR]

Over-the-horizon radars (OTHRs) often operate in the presence of interference that is nonstationary over the coherent processing interval (CPI). In this case, effective adaptive beamforming requires intra-CPI updates to the spatial weight vector to track changes in the interference spatial structure. However, these weight vector changes must be constrained to prevent modulating the clutter signal and drastically reducing subclutter visibility. These additional constraints require a model of the clutter signal. Existing adaptive beamforming algorithms either explicitly or implicitly rely on a scalar multivariate autoregressive (MVAR) model, which is based on typical observations made by mid-latitude OTHRs. However, high-latitude OTHRs often observe angle-Doppler coupled clutter, for which the scalar MVAR model does not apply. This article investigates the ramifications of angle-Doppler coupling for spatial adaptive processing (SAP), which results in the proposal of a new SAP algorithm. The efficacy of the new algorithm is compared to existing methods through simulation. [ABSTRACT FROM AUTHOR]

The range resolution of radar is inversely proportional to the swept bandwidth. However, this bandwidth may not be available due to a variety of reasons, including spectrum congestion and lack of instantaneous bandwidth despite access to a larger tunable bandwidth. Existing approaches to achieving high-range resolution include bandwidth extrapolation, ultrawideband coherent processing, and spectral splicing of narrowband stepped-frequency pulses. In this article, we achieve high-range resolution of a wideband chirp from a sequence of narrowband pulses using coherent-phase extension of the beat tones of an FMCW dechirper. By phase matching the beat tones across pulse boundaries, the algorithm trades a longer observation interval for a smaller swept bandwidth. Phase matching of the short beat tones is applied in two steps to first obtain the coarse estimate of the beat frequencies which are then used as the starting point in the formation of the range-Doppler map that now enjoys the two-dimensional fast-Fourier transform (2-D-FFT) gain. With this approach, a fraction of the total bandwidth to obtain a range resolution of a wideband chirp is used. Using both simulations and experimental data, the proposed high-resolution algorithm is applied to a narrowband chirp sequence with bandwidth $B$ to generate range-Doppler maps with range resolution corresponding to a wideband chirp sequence of bandwidth $NB$. [ABSTRACT FROM AUTHOR]

In this article, we propose kernel maximum correntropy based nonlinear estimators for range and velocity estimation in non-Gaussian clutter and system nonlinearity. The proposed estimators are analyzed for linear frequency modulated and stepped frequency radar systems. Additionally, an adaptive update equation is derived for optimization of the kernel width, which further lowers the dictionary size and the variance of the proposed estimators. For performance evaluation of the proposed estimators, an expression is derived for the Cramer–Rao lower bound using a modified Fisher information matrix. [ABSTRACT FROM AUTHOR]

We consider the problem of minimizing the disturbance power at the output of the matched filter in a single antenna cognitive radar set-up. The aforementioned disturbance power can be shown to be an expectation of the slow-time ambiguity function (STAF) of the transmitted waveform over range-Doppler bins of interest. The design problem is known to yield a nonconvex quartic function of the transmit radar waveform. This STAF shaping problem becomes even more challenging in the presence of practical constraints on the transmit waveform such as the constant modulus constraint (CMC). Most existing approaches address the aforementioned challenges by suitably modifying or relaxing the design cost function and/or the CMC. In a departure from such methods, we develop a solution that involves direct optimization over the nonconvex complex circle manifold, i.e., the CMC set. We derive a new update strategy [quartic-gradient-descent (QGD)] that computes an exact gradient of the quartic cost and invokes principles of optimization over manifolds toward an iterative procedure with guarantees of monotonic cost function decrease and convergence. Experimentally, QGD can outperform state-of-the-art approaches for shaping the ambiguity function under the CMC while being computationally less expensive. [ABSTRACT FROM AUTHOR]

This paper considers the localization of a moving target using a forward scatter radar consisting of a transmitter and an array antenna receiver. A direct positioning method based on maximum likelihood (ML) estimation is proposed and compared with the conventional two-step method in which the primary parameters, including Doppler shift and angle of arrival, should be determined in the first step. Moreover, closed-form expressions for Cramer–Rao lower bound of both methods are derived. The aforementioned methods are comprehensively compared in terms of positioning accuracy and computational complexity. Theoretical performance study, including determining the minimum required observation time for achieving a certain positioning error level and analyzing the best possible positioning accuracy in extreme scenarios, is carried out. The results of numerical simulations demonstrate that the proposed direct approach is more precise compared to the two-step method and can achieve higher resolution levels. [ABSTRACT FROM AUTHOR]

This paper is devoted to the estimation of target motion parameters with a forward scatter radar (FSR). To provide an upper bound for the estimation performance, a closed-form expression of the Cramér–Rao lower bound (CRLB) is provided for the main target signal parameters, namely Doppler rate, baseline crossing instant, and main lobe width parameter of the target amplitude modulation pattern. This is performed by operating on the signal at the output of the standard FSR processing scheme, namely on the crystal video detector signal: the received signal, which is passed through a square-law envelope detector followed by a DC removal filter. The estimate of the kinematic parameters of moving targets that follow a linear trajectory can be obtained by inverting the relationship between these parameters and the previously estimated target signal parameters. Especially, two FSR configurations are investigated: single-node FSR configuration and dual-baseline FSR configuration with a small angular separation between the two baselines. The closed-form expression of the corresponding CRLB is derived by using a linearized version of the same inverse transformation. Finally, a practical estimator is presented, based on a two-dimensional filter bank, and its performance is compared with the derived CRLB. The results show that unbiased and highly accurate estimates of the kinematic parameters are obtained. The feasibility and the effectiveness of this estimation scheme is demonstrated by applying this technique to recorded live data acquired with a dual-baseline FSR configuration exploiting FM signals as a waveform of opportunity. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of radar range-Doppler imaging in the presence of clutter. Specifically, we formulate the range-Doppler imaging problem as that of recovery of a sparse vector contaminated by clutter in addition to noise. We propose a sparse Bayesian learning (SBL)-based algorithm to jointly obtain the range-Doppler image, variance of the noise, and covariance matrix of the clutter. Furthermore, we adapt a simple pruning mechanism that reduces the computational cost and improves the convergence speed. [ABSTRACT FROM AUTHOR]

Detection and localization in urban environments is a very recent radar problem. In this paper, we investigate the possibility of detecting and locating targets not in direct line of sight (NLOS) areas with a single portable radar by exploiting multipath returns. We propose two algorithms, which handle the information provided by multipath returns in different ways to detect and estimate the NLOS target position. We also present an original method to select the number of paths to take into account in the algorithms in order to maximize detection probabilities. Numerical results show good efficiency of the proposed algorithms for problems of both detection and localization. We show that applying these algorithms improves detection performance compared to a classic matched filter in a typical urban scenario. Experimental results on a real dataset allow us to validate our multipath model in urban environments, and in particular to show that it is possible to retrieve the target location even with rough knowledge of the scene geometry. [ABSTRACT FROM AUTHOR]

In previous works, methods were explored for position estimation utilizing satellite-borne signals of opportunity, mainly the global positioning system (GPS). The GPS signal was exploited for use in a multistatic passive coherent location (PCL) system. The GPS signal is especially attractive for PCL applications because of the native capability to produce position and velocity estimation. This paper examines the signal specifications for PCL implementation and explores the potential limitations of the proposed solutions. GPS specific methods are developed for multistatic PCL velocity estimation in a three-dimensional plane. The method developed is combined with previously completed work of GPS PCL position estimation for a complete system design in range and Doppler. The PCL system is evaluated against conventional GPS position estimation and velocity estimation and proves to have comparable metrics of performance. Analysis and simulation are performed for verification and validation of the developed methods. [ABSTRACT FROM AUTHOR]

Relationship between the delay and Doppler shift with the radar return is nonlinear in nature. Therefore, a nonlinear estimator based on sparse kernel least mean square algorithm is proposed. Further, an adaptive kernel width optimization technique is proposed to lower the computational complexity and for simple implementation. An expression for the Cramer–Rao lower bound is derived and validated for the proposed estimator over linear frequency modulated, and orthogonal frequency division multiplexed radar systems. [ABSTRACT FROM AUTHOR]

Future radar transmitters must be adaptive and reconfigurable in real time to be able to share spectrum dynamically with wireless communications. We demonstrate the joint, back-and-forth optimization of the radar transmitter waveform and circuitry in a combined algorithm that can be used for real-time reconfiguration. While previously developed methods consider the waveform and circuit separately, resulting in emphasis on one of the criteria [ambiguity function (AF) or power efficiency], we show that the joint optimization of the circuit and waveform allows both the radar AF and circuit power-added efficiency (PAE) criteria to be gradually improved during the optimization. Measurement results are presented and analyzed to assess the convergence of the PAE and AF least-squares error, as compared to the AF template during an optimization under spectral mask and peak-to-average power ratio constraints. [ABSTRACT FROM AUTHOR]

For jointly estimating angle-Doppler information, two-dimen-sional multiple signal classification (MUSIC) is often applied, which requires an exhaustive grid search over angle-Doppler domain. To mitigate the computational complexity and enhance the estimation performance, we modify two-dimensional MUSIC in three steps. First, instead of using two-dimensional spectral search, it is converted to two consecutive polynomial root-finding problems. Second, the degree of the polynomial in the first root-finding stage is undesirably high in general; hence, we approximate it to a lower order polynomial through discrete Fourier transform. Finally, further enhancement can be achieved by having the closest approximation of null-spectrum function by assigning unequal weight coefficients. Cramer–Rao bound is derived for joint angle-Doppler estimation as a benchmark in our performance analysis. [ABSTRACT FROM AUTHOR]

In a low-angle target parameter estimation scenario, the backscattered signals from targets are often distorted due to clutter and multipath, which significantly degrades the performance of direction-of-arrival (DOA) estimation. In general, the backscattered multipaths are modeled as coherent signals with respect to the direct path. Decorrelation algorithms such as spatial smoothing and matrix reconstruction can mitigate the effect of multipath. However, most of these methods will perform poorly or even fail for solving parameter estimation problem of low-angle targets in complex terrain where there are rich multipath scatterings. This paper presents a novel method that combines time reversal (TR) technique, coherent signal-subspace method (CSM), and multiple signal classification algorithm to perform DOA estimation in a low-angle target scenario. The TR technique takes advantage of multipath echoes recorded by a sensor array and adaptively adjusts TR probing waveforms to increase the signal-to-noise ratio in a rich scattering environment. Moreover, the CSM method compresses the energy of a signal into a predefined subspace to exploit the full time-bandwidth product of signal sources and cope with coherent wavefronts. As a result, the proposed new DOA estimation algorithm outperforms significantly the conventional methods. The Cramer–Rao bounds analysis and numerical simulations commendably validate the accuracy and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Radar-based activity recognition is a problem that has been of great interest due to applications such as border control and security, pedestrian identification for automotive safety, and remote health monitoring. This paper seeks to show the efficacy of micro-Doppler analysis to distinguish even those gaits whose micro-Doppler signatures are not visually distinguishable. Moreover, a three-layer, deep convolutional autoencoder (CAE) is proposed, which utilizes unsupervised pretraining to initialize the weights in the subsequent convolutional layers. This architecture is shown to be more effective than other deep learning architectures, such as convolutional neural networks and autoencoders, as well as conventional classifiers employing predefined features, such as support vector machines (SVM), random forest, and extreme gradient boosting. Results show the performance of the proposed deep CAE yields a correct classification rate of 94.2% for micro-Doppler signatures of 12 different human activities measured indoors using a 4 GHz continuous wave radar—17.3% improvement over SVM. [ABSTRACT FROM AUTHOR]

The Radon–Fourier transform (RFT) with a long coherent integration time has recently been proposed for detecting a moving target with an across range cell (ARC) effect. However, without effective clutter suppression, clutter will also be integrated via the RFT, which may affect weak target detection. Based on the maximal signal-to-clutter-plus-noise ratio (SCNR) criteria, a novel adaptive RFT (ARFT) is proposed in this paper to effectively detect a “low-observable” target in a clutter background. The proposed ARFT can combine RFT and adaptive clutter suppression by introducing an optimal filter weight, which is determined from the clutter's covariance matrix as well as a steering vector for a moving target with the ARC effect. In the transformed range-velocity space, the proposed ARFT can suppress background clutter and optimally integrate the target's energy. Nevertheless, with the increase in the integration time, the ARFT needs to address two difficulties in its real implementation. One is the lack of independently and identically distributed (i.i.d.) training samples in a heterogeneous clutter background, and the other is that the computational complexity is too high due to the large number of pulse samples. Therefore, a subaperture ARFT (SA-ARFT) is further proposed in this paper. It divides all coherent pulse samples into several subapertures and accomplishes adaptive clutter suppression in each subaperture. Subsequently, SA-ARFT implements coherent integration among the outputs of different subapertures. The proposed SA-ARFT method can obtain a similar SCNR improvement factor (SCNR IF) with a large number of i.i.d. training samples, while it can obtain a much higher SCNR IF than the ARFT with limited i.i.d. training samples and much lower computational complexity in a heterogeneous clutter background. Finally, some numerical results are provided to demonstrate the effectiveness of the two proposed methods. [ABSTRACT FROM AUTHOR]

The forward scatter radar (FSR) configuration is especially appealing for the detection of low-observable targets since it provides well-known properties for the radar cross section, which includes enhancements with respect to the monostatic and/or moderate bistatic configurations, as well as robustness to the target material and detailed geometrical characteristics. Due to the separation of a transmitter and a receiver, it is customary to use a detection scheme based on a square-law envelope detector followed by an appropriate matched filter, which we address as a crystal video detector (CVD) based on traditional terminology. This paper provides an accurate analytical expression for the detection performance of the FSR target detection using the CVD in terms of both the probability of false alarm $(P_{{\rm{fa}}})$ and the probability of detection $(P_{{\rm{d}}})$ in order to support performance prediction and FSR system design. The derived expressions are validated by comparison to Monte Carlo simulations under two different geometrical scenarios. Moreover, the comparison of the CVD performance to an ideal optimum detector (upper bound for the FSR achievable detection performance) shows the geometrical conditions, where the CVD suffers significant detection losses so that alternative detectors should be investigated. Finally, to remove the need to operate the CVD with a fixed detection threshold, two fully adaptive detectors are derived, based on the structure of the CVD scheme, which are shown to provide a constant false alarm rate (CFAR). The performance of these CFAR detectors in terms of $P_{{\rm{fa}}}$ and $P_{{\rm{d}}}$ are provided in closed form and validated through Monte Carlo simulations, showing quite small losses with respect to the fixed-threshold CVD. The application to real data acquired by a passive FSR based on frequency-modulated signals is used to show the practical effectiveness and consistency. [ABSTRACT FROM AUTHOR]

In this paper, a sparsity-driven method of micro-Doppler analysis is proposed for dynamic hand gesture recognition with radar sensors. First, sparse representations of the echoes reflected from dynamic hand gestures are achieved through the Gaussian-windowed Fourier dictionary. Second, the micro-Doppler features of dynamic hand gestures are extracted using the orthogonal matching pursuit algorithm. Finally, the nearest neighbor classifier is combined with the modified Hausdorff distance to recognize dynamic hand gestures based on the sparse micro-Doppler features. Experiments with real radar data show that the recognition accuracy produced by the proposed method exceeds 96% under moderate noise, and the proposed method outperforms the approaches based on principal component analysis and deep convolutional neural network with small training dataset. [ABSTRACT FROM PUBLISHER]

Radar tracking of aircraft targets at low elevation angles can be complicated by clutter from wind turbines, which we define to be clutter. In this paper, we study detection in a staring pulse-Doppler radar. By exploiting the second-order correlation structure of this wind-turbine clutter we derive a target detector that uses a sequence of adaptive coherence scores. The detector uses a multipulse coherence statistic consisting of an incoherent geometric average of coherently computed adaptive coherence scores. The detector compares favorably to a multipulse coherence detector that uses no modeling or estimation of the clutter. [ABSTRACT FROM PUBLISHER]

Sparse signal representation is used to coherently separate the main rotor blade components of a helicopter from the composite data of complex time series radar returns. Received signals of this type typically consist of returns from the rotating main and tail rotor blades, the helicopter body, and other residual components which may overlap in time and frequency, thus making it difficult for conventional time–frequency separation techniques to be applied for the signal separation. In the proposed algorithm, a sparse signal representation is applied with the use of tunable Q wavelet transform to construct the dictionary, and basis pursuit denoising is used for the signal reconstruction of the component of interest. The algorithm shows very effective separation of the main rotor blade component from the composite radar returns, which is demonstrated using both simulated and real radar data at X-band. [ABSTRACT FROM AUTHOR]

A complementary set of $K$ binary $\pm 1$ codes of length $N$ has the useful property that the sum of the autocorrelation sequences of the codes has only one nonvanishing element, its size-$KN$ peak. The $N\times K$ matrix whose columns are the codes of a binary complementary set, arranged in order, is the code set's complementary code matrix (CCM). One might ask for which $K$ and $N$ such matrices exist. A simple necessary condition for the existence of an $N\times K$ CCM is introduced, involving the sum of the squares of the imbalance values of the codes in the set (the imbalance of a binary $\pm 1$ code being the difference between the number of 1 and number of $-1$s in the code). The one-to-one relationship between binary CCMs and binary complementary code sets allows the necessary condition for the $N\times K$ CCM existence to extend to a necessary condition for sets of $K$ complementary code sets of length $N$. We examine the sum-of-squares condition for the separate cases of $N$ even and $N$ odd. The odd case is especially interesting, since representations in terms of sums of squares of odd integers are equivalent to representations as sums of triangular numbers, a subject of recent research in Number Theory. Furthermore, we exhibit a refinement of the existence condition in terms of the imbalance values of pairs of interlaced subcodes. This refinement is new, to the best of our knowledge. Finally, we investigate whether odd-length complementary code sets exist for $K>2$, unlike the Golay case of $K=2$ where odd-length sets cannot exist. We easily find, by computer search, a four-code set of length 15, suggesting that these are likely not uncommon. [ABSTRACT FROM AUTHOR]

Presents the table of contents for this issue of the publication. [ABSTRACT FROM PUBLISHER]

This paper addresses the coherent integration problem for detecting a high-speed target, involving range walk (RW) within the coherent processing time. A fast method based on sequence reversing transform is proposed to eliminate the RW and achieve the coherent accumulation. The proposed method is simple and fast since it can be easily implemented by using complex multiplications, the fast Fourier transform (FFT) and the inverse FFT. Compared with the Radon–Fourier transform and moving target detection methods, the presented algorithm can avoid the blind speed sidelobe and make a good balance between the computational cost and the detection ability. Finally, several simulations are provided to demonstrate its effectiveness. [ABSTRACT FROM PUBLISHER]

This paper demonstrates the feasibility and effectiveness of forward-scatter radar (FSR) target detection based on the signals of opportunity made available by standard radio and TV broadcast transmission stations. This passive FSR (P-FSR) operation is obtained by means of a simple and robust correlation process based on self-mixing. This is shown to be very effective in extracting the characteristic FSR modulation produced by airborne targets, from the signals received from frequency modulated, digital audio broadcasting, and digital video broadcasting transmitters of opportunity. Target detectability is discussed as a function of the carrier frequency, the target size, and its height at the baseline crossing. Experimental results are shown using a wide variety of sources of opportunity, target types, baselines, and receiver configurations. The target signatures obtained from the different illuminators are compared and ways of extracting the kinematic parameters of the aircraft are discussed. This validates the claimed effectiveness and robustness of the P-FSR with the presented processing scheme. [ABSTRACT FROM PUBLISHER]