Showing papers on "Moving target indication published in 2016"

Micro-Doppler based detection and tracking of UAVs with multistatic radar

Abstract: This paper presents an approach for detection and tracking a micro-UAV using the multistatic radar NetRAD. Experimental trials were performed using NetRAD allowing for analysis of real data to assess the difficulty of detection and tracking of a micro-UAV target. The UAV detection is based on both time domain and micro-Doppler signatures, in order to enhance the discrimination between ground clutter and UAV returns. This micro-Doppler based procedure is shown to improve the clutter/target discrimination, in comparison to a Doppler-shift based procedure. The tracking approach is able to compensate for the limited quality measurement generated by each bistatic pair by fusing the measurements available from multiple bistatic pairs.

Space-Time Adaptive Processing With Vertical Frequency Diverse Array for Range-Ambiguous Clutter Suppression

Abstract: A high-pulse-repetition-frequency (PRF) radar can handle the high Doppler frequencies of clutter echoes received by a fast-moving airborne radar. However, high-PRF radar causes range ambiguity. In addition, the clutter is range dependent when the airborne radar works in a forward-looking geometry. The range ambiguity and range dependence will lead to severe performance degradation of the traditional space-time adaptive processing (STAP) methods. In this paper, a vertical frequency diverse array (FDA), which applies frequency diversity in the vertical of a planar array, is explored to circumvent the range ambiguity problem in STAP radar. A range-ambiguous clutter suppression approach is devised, which consists of vertical spatial frequency compensation and pre-STAP filtering. In the vertical-FDA radar, the vertical spatial frequency depends not only on the depression angle but also on the slant range. By using this characteristic, the range-ambiguous clutter can be separated in the vertical spatial frequency domain, and then, clutter suppression is achieved for each separated range region. As a result, both problems of range ambiguity and range dependence are solved. Simulation results are provided to demonstrate the effectiveness of the proposed method.

A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar

Abstract: For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method.

Shape-parameter-dependent coherent radar target detection in K-distributed clutter

Abstract: In this paper, shape-parameter-dependent matched filter (MF) detectors are proposed for moving target detection in K-distributed clutter, which are specified by a single parameter α [0, 1], the α-MF detectors for short. The α-MF detectors include the MF and normalized matched filter (NMF) detectors as special examples with α = 0 and 1. The parameter α can be chosen to match clutter characteristics. An empirical formula is given that the optimal parameter α equals the number of integrated pulses divided by it plus the shape parameter of K-distributed clutter. It is proved that the α-MF detectors are constant false alarm rate (CFAR) with respect to the scale parameter, clutter covariance matrix, and Doppler steering vector. The properties of adaptive α-MF (α-AMF) detectors are discussed. For K-distributed clutter, the optimal α-MF detectors are superior to the MF and NMF detectors and are comparable with the optimal K-distributed detectors (OKDs) of high computational cost. Finally, real high-resolution sea clutter data are available to verify the proposed detectors. The optimal α-AMF detectors under K-distributed clutter model are competitive in performance with the adaptive generalized likelihood ratio test linear threshold detectors (GLRT-LTDs) that are optimal for the compound-Gaussian clutter with the inverse Gamma texture.

Slow radar target detection in heterogeneous clutter using thinned space-time adaptive processing

Abstract: The authors address the problem of slow target detection in heterogeneous clutter through dimensionality reduction. Traditional approaches of implementing the space-time adaptive processing (STAP) require a large number of training data to estimate the clutter covariance matrix. To address the issue of limited training data especially in the heterogeneous scenarios, they propose a novel thinned STAP through selecting an optimum subset of antenna-pulse pairs that achieves the maximum output signal-to-clutter-plus-noise ratio. The proposed strategy utilises a new parameter, named spatial spectrum correlation coefficient, to analytically characterise the effect of space-time configuration on STAP performance and reduce the dimensionality of traditional STAP. Two algorithms are proposed to solve the antenna-pulse selection problem. The effectiveness of the proposed strategy is confirmed by extensive simulation results, especially by utilising the multi-channel airborne radar measurement data set.

Advanced multipath clutter cancellation in OFDM-based passive radar systems

Abstract: We present an advanced algorithm to suppress multipath clutter in passive radar systems using OFDM signals for surveillance. Multipath clutter signals not only lead to enormous zero Doppler signals in the range Doppler domain, they also induce intense side lobes when the multipath signals have additional small Doppler shifts to the reference signal and thereby can mask targets with small Doppler frequencies and small SNR. The proposed algorithm, denominated as Enhanced Cancellation Algorithm by Carrier and Doppler Shift (ECA-CD), removes multipath clutter signals and reduces its side lobes. Its implementation and experimental tests show the effectiveness of multipath signal suppression in real time.

NetRAD: Monostatic and Bistatic Sea Clutter Texture and Doppler Spectra Characterization at S-Band

Abstract: This paper describes the analysis performed on coherent simultaneously recorded monostatic and bistatic sea clutter data. The data were generated using a networked pulsed radar system, namely, NetRAD. This analysis is completed in both the temporal and Doppler domains, and the parameters characterized are compared between multiple bistatic angles and different polarizations. The K-distribution model is used to assess the variation in the clutter amplitude statistics between multiple bistatic data and the corresponding monostatic data. Key characteristics of the Doppler data, such as the spectrum width, center of gravity (CoG), and variance of the spectral width, are evaluated as a function of bistatic angle allowing novel relationships to be defined. The results conclude that the bistatic Doppler data have a lower K-distribution shape parameter in the majority of bistatic angles compared with the simultaneous monostatic data. In addition, novel trends in the relationship between the clutter spectrum CoG and the clutter intensity are presented.

Moving Target Detection via Efficient ATI-GoDec Approach for Multichannel SAR System

Abstract: Clutter suppression and ground moving target indication (GMTI) are challenging tasks for multichannel synthetic aperture radar (MC-SAR) systems. In recent years, robust principal component analysis (RPCA), such as the augmented Lagrange multiplier method (ALM) and go decomposition (GoDec) algorithm, has drawn considerable attention for its excellent performance in distinguishing the different parts from a set of correlative database. In this letter, an efficient along-track interferometry GoDec (ATI-GoDec) approach is proposed for GMTI in MC-SAR systems under a strong clutter background. The proposed method can be separated into two sections: the predetection and the postdetection. The predetection by an efficient ATI RPCA method can decrease missing targets, and postdetection with a novel magnitude and phase (M&P) detection has the ability to reduce the false targets. As a result, the proposed method can provide a more robust performance by a comparison to the traditional ATI detection. It can also widen the tolerant values of the preset cardinality and decrease the probability of false alarm compared with the conventional GoDec algorithm. Moreover, the proposed method only takes several iterations to reach the convergence by solving the optimization problem of the RPCA model, which makes it more efficient than the previous RPCA methods. The results by applying the proposed method into a set of real SAR data are consistent with the analysis presented in this letter.

Simultaneous Stationary Scene Imaging and Ground Moving Target Indication for High-Resolution Wide-Swath SAR System

Abstract: In synthetic aperture radar (SAR) images, moving targets are usually smeared and/or imaged at incorrect positions due to the target motions during the SAR integration time. Moreover, since a high-resolution wide-swath SAR system is operated with a rather low pulse repetition frequency, a moving target will cause multiple ghost targets in the reconstructed SAR image. A new space–time adaptive processing framework is proposed in this paper for removing moving target artifacts in SAR images. In this new framework, the dynamic steering vector concept is proposed. In addition, this paper develops a moving target processing scheme for clutter suppression and moving target imaging and location for a high-resolution wide-swath SAR system. Finally, we locate the well-focused moving targets at the stationary scene image without any disturbing artifacts. The simulated and real data are used to validate the effectiveness of our proposed method.

Analysis of CFAR techniques

Abstract: In radar the reflected signal is received by the antenna which is amplified, down converted and then the required signal is extracted (video signal). The video signal is then passed through Moving Target Indicator (MTI) processor which suppresses clutter. The post-MTI data is passed through Constant False Alarm Rate (CFAR) processor which qualifies echoes as targets or otherwise. The role of CFAR processor is to determine a threshold, above which any return can be considered to be from target. If this threshold is too low, more targets will be detected at the expense of more false alarms. Conversely, if the threshold is set too high, then fewer targets will be detected but the number of false alarms will be less. The distribution of the clutter can be approximated by certain probability distribution functions, where each medium follows a different probability distribution. We shall investigate important CFAR processing techniques in Gaussian noise and Rayleigh clutter. The threshold is set adaptive, that is the threshold is raised or lowered, to maintain a required Probability of False Alarm (Pfa). This paper discusses various CFAR processing techniques, by applying them to raw video of real radar, analyzing advantages and disadvantages of each technique.

Ground Moving Target Indication in SAR Images With Symmetric Doppler Views

Abstract: A new algorithm is presented to indicate ground moving targets in synthetic aperture radar (SAR) images. Two symmetric SAR images, one is referred to as a positive Doppler view and the other as a negative Doppler view, are generated by refocusing the positive Doppler plane and the negative Doppler plane, respectively. In the two Doppler views, the backgrounds have the same intensity except that their azimuth resolution becomes half of that of the original image, but the moving targets appear at different positions and have different intensities due to their different Doppler contents arising from nonzero Doppler centroid caused by across-track motion. Therefore, moving targets can be indicated by the patch-by-patch intensity comparison of the two Doppler views. The results of the simulated and real data confirm that this algorithm is effective and efficient.

Joint radar-communications information bounds with clutter: The phase noise menace

Abstract: We model the effects of phase noise on clutter cancellation and study the overall impact it has on the radar estimation rate. Cooperative bounds involving radar cancellation for additional communications access are impacted by complicating the overall model. We assume the clutter is static with small intrinsic clutter motion (ICM). Treating the clutter cancellation residual due to intrinsic clutter motion and phase noise as an additional noise source, the radar estimation rate is negatively impacted. This clutter cancellation residual further degrades the communications channel, affecting the communications data rate as well. We also study the relationship between the clutter cancellation residual and the range of the scatterer.

Radar phase noise modeling and effects–part I: MTI filters

Abstract: Random and unwanted fluctuations, which perturb the phase of an ideal reference sinusoidal signal, may cause significant performance degradation in radar systems exploiting coherent integration techniques. To quantify the resulting performance loss, we develop a fast-time/slow-time data matrix radar signal representation, modeling the undesired phase fluctuations via multivariate circular distributions and describing the phase noise power spectral density (PSD) through a composite power-law model. Hence, we accurately predict the performance degradation experienced by moving target indication (MTI) algorithms for clutter cancellation, providing a closed form expression for the improvement factor I. The subsequent analysis shows that phase noise affects I directly through its characteristic function (CF). Additionally, I shares a robust behavior with respect to the actual phase noise multivariate circular distribution, as long as the phase noise PSD correctly represents the available measurements.

Coherent radar processing in sea clutter environments, part 1: modelling and partially adaptive STAP performance

Abstract: Performance of space–time adaptive processing (STAP) with adaptive matched filter detection for maritime surveillance is assessed using simulated maritime surface targets embedded in real radar sea clutter data and compared with conventional pulse-Doppler processing. Pre-Doppler and post-Doppler suboptimal STAP are examined, with pulse repetition interval (PRI)-staggered post-Doppler shown to provide best overall detection and constant false alarm rate performance. A two-component clutter model fit is used to explain variations of clutter characteristics and detector performance with Doppler frequency.

Ground target tracking with RCS estimation based on signal strength measurements

Abstract: The discrimination of closely spaced targets is a major challenge in the ground target-tracking domain based on measurements of airborne ground moving target indication radar. Being a standard output of modern radar systems, the measured signal strength of a radar detection can be used to estimate the characteristic mean radar cross section (RCS) of a ground target, which is then used as additional target attribute information to improve the tracking performance in situations with closely spaced targets. For this method to work, the fluctuations of the target RCS are assumed to follow the analytically tractable Swerling-I and Swerling-III cases. In this work, the RCS estimation scheme originally developed for air targets [1, 2] is generalized to ground-moving objects and then implemented into the Gaussian mixture cardinalized probability hypothesis density filter. The performance of the resulting algorithm is analyzed based on single and multiple-target simulation scenarios. In the latter case, a modified version of the optimal subpattern assignment metric that also accounts for labeling errors is used.

Joint Monostatic and Bistatic STAP for Improved SAR-GMTI Capabilities

Abstract: This paper proposes a novel simultaneous monostatic and bistatic ground moving target indication (GMTI) mode for improved target detection and imaging capability. The mode uses an airborne multichannel radar system and a stationary transmitter. Both systems transmit simultaneously on adjacent frequency bands, and the airborne multichannel system receives both its monostatic echoes and the bistatic returns. Geometrical diversity between the monostatic and bistatic measurements enhances moving target detection capabilities. Moreover, for movers detected in both data sets, an estimation of the target velocity vector (i.e., velocity and direction of motion) can be performed. By simply extracting a single-channel data set, this also allows correct focusing of moving targets both in monostatic and bistatic data sets, if synthetic aperture radar GMTI capability is required. Consequently, situational awareness over the observed area is greatly improved. The effectiveness of the proposed technique is analyzed both from a theoretical point of view and by means of an ad hoc experiment conducted by the Fraunhofer Institute for High Frequency Physics and Radar Techniques (FHR) in fall 2013.

Joint equalization filters that mitigate waveform-diversity modulation of clutter

Abstract: Moving-target indication radars require advanced signal processing to be able to use pulse-to-pulse waveform diversity. The primary challenge is range-sidelobe modulation (RSM) of clutter. Because range sidelobes differ on each pulse, clutter energy that leaks into range sidelobes cannot be cancelled. We find that higher target SINR can be be obtained by joint design of the pulse-compression filters to obtain impulse responses that match across pulses. The proposed filters can reduce RSM by 5–10 dB compared to low-sidelobe mismatch filters designed separately for each pulse.

Dual-Platform Large Along-Track Baseline GMTI

Abstract: In this paper, a novel method for traffic monitoring using a spaceborne dual-platform synthetic aperture radar system is presented. The chosen along-track baseline between both platforms needs to be on the order of ten to several tens of kilometers, resulting in a time lag of several seconds between the target observations. With the proposed method, the true geographical positions, the velocities, and the moving directions of the detected moving targets can be estimated with high accuracy. The method has been verified and evaluated using experimental data acquired with the German TerraSAR-X/TanDEM-X radar satellite formation. The results are compared with ground truth reference data.

A Ground Moving Target Detection Approach Based on Shadow Feature With Multichannel High-Resolution Synthetic Aperture Radar

Abstract: With the observation distance of the radar increasing, the multichannel high-resolution synthetic aperture radar system may suffer from the reduction of the target signal-to-noise ratio, which leads to degradation in the detection performance for ground moving target indication (GMTI). Fortunately, the shadow feature, apart from the amplitude and interferometric phase of a moving target, may be available to improve the performance for target detection. In this letter, according to the geometric relationships between the moving object and its shadow in position and size, a shadow-aided method for GMTI is proposed. In addition, an efficient shadow detection method based on multifeature fusion is discussed to improve the shadow detection performance. Finally, numerical simulation results show that the shadow-aided method has a better detection performance, compared with the traditional detection algorithms.

Virtual multichannel SAR for ground moving target imaging

Abstract: Slow moving ground targets are invisible within synthetic aperture radar (SAR) images since they appear defocused and their backscattered signal completely overlap the focused ground return. In order for this targets to be detected and refocused the availability of some spatial degrees of freedom is required. This allows for space/slow time processing to be applied to mitigate the ground clutter. However, multichannel SAR (M-SAR) systems are very expensive and the requirements in terms of baseline length can be very restrictive. In this study a processing scheme that exploits high PRF single channel SAR system to emulate a multichannel SAR is presented. The signal model for both target and clutter components are presented and the difference with respect to an actual M-SAR are highlighted. The effectiveness of the proposed processing is then demonstrated on simulated a measured dataset.

Detection and localization of multiple short range targets using FMCW radar signal

Abstract: In this paper, a 24 GHz frequency-modulated continuous wave radar is used to detect and localize both stationary and moving targets. Depending on the application, the implemented software offers different modes of operation. For example, it can simply output raw data samples for advanced offline processing or directly carry out a two dimensional fast Fourier transform to estimate the location and velocity of multiple targets. To suppress clutter and detect only moving targets, two methods based on the background reduction and the slow time processing techniques are implemented. A trade-off between the two methods is presented based on their performance and the required processing time.

Robust SAR STAP via Kronecker decomposition

Abstract: This paper proposes a spatiotemporal decomposition for the detection of moving targets in multi-antenna synthetic aperture radar (SAR). As a high-resolution radar imaging modality, SAR detects and localizes nonmoving targets accurately, giving it an advantage over lower-resolution ground-moving target indication (GMTI) radars. Moving target detection is more challenging due to target smearing and masking by clutter. Space-time adaptive processing (STAP) is often used to remove the stationary clutter and enhance the moving targets. In this work, it is shown that the performance of STAP can be improved by modeling the clutter covariance as a space versus time Kronecker product with low-rank factors. Based on this model, a low-rank Kronecker product covariance estimation algorithm is proposed, and a novel separable clutter cancelation filter based on the Kronecker covariance estimate is introduced. The proposed method provides orders of magnitude reduction in the required number of training samples as well as improved robustness to corruption of the training data. Simulation results and experiments using the Gotcha SAR GMTI challenge dataset are presented that confirm the advantages of our approach relative to existing techniques.

Ground Moving Target Detection and Imaging Using a Virtual Multichannel Scheme in HRWS Mode

Abstract: Along-track multichannel synthetic aperture radar is usually used to achieve ground moving target detection and imaging. Nevertheless, there is a design dilemma between azimuth high resolution and wide swath (HRWS). To solve this problem in HRWS mode, we introduce a virtual multichannel (VMC) scheme. For each virtual channel, the low real pulse repetition frequency (PRF) improves the ability of resolving range ambiguity for wide-swath, and the high virtual PRF improves the capability of resolving Doppler ambiguity for azimuth high resolution. For multiple virtual channels, strong ground clutter is eliminated by the joint VMC processing. Furthermore, a detailed signal model of a moving target in the virtual channel is given, and the special false-peak effect in the azimuthal image is analyzed. Moreover, we propose a novel ground moving target processing method based on the VMC scheme and the clutter suppression interferometry (CSI) technique, which is called VMC-CSI. The integration of detection, location, velocity estimation, and imaging for ground moving targets can be achieved. Accounting for the unresolved main peak and false peak for a moving target, in the VMC-CSI method, we adopt a two-step scheme to estimate the radial velocity and along-track velocity, namely, rough estimation and precise estimation. Meanwhile, considering the same interferometric phases of the main peak and the false peak, we use false peaks first for the robustness of initial azimuth location estimation and remove false peaks afterward. Numerical simulations are provided for testing the effect of the false peak and the effectiveness of VMC-CSI.

An enhanced particle filtering method for GMTI radar tracking

Abstract: This paper investigates the problem of ground vehicle tracking with ground-moving target indicator (GMTI) radar. In practice, the movement of ground vehicles may involve several different maneuvering types (acceleration, deceleration, standstill, etc.). Consequently, the GMTI radar may lose measurements when the radial velocity of the ground vehicle is below a threshold, i.e., falling into the Doppler blind region. In this paper, to incorporate the information gathered from normal measurements and knowledge on the Doppler blindness constraint, we develop an enhanced particle filtering method for which the importance distributions are inspired by a recent noise-related Doppler blind (NRDB) filtering algorithm for GMTI tracking. Specifically, when constructing the importance distributions, the proposed particle filter takes the advantages of the efficient NRDB algorithm by applying the extended Kalman filter and its generalization for interval-censored measurements. In addition, the linearization and Gaussian approximations in the NRDB algorithm are corrected by the weighting process of the developed filtering method to achieve a more accurate GMTI tracking performance. The simulation results show that the proposed method substantially outperforms the existing methods for the GMTI tracking problem.

On the design of staggered moving target indicator filters

Abstract: The problem of moving target indicator (MTI) filter design for radar systems with non-uniform (staggered) pulse repetition intervals is examined. The goal is to realise and then utilise a trade-off in the design of MTI filter between the conflicting requirements of high suppression of undesired signal (clutter echo) and minimal suppression of desired signal (target echo). To that aim, three design methodologies, namely, least squares, convex optimisation and min–max error, are studied. The numerical results indicate that the presented designs yield high-performance MTI filters which are easily applicable to a variety of operational scenarios. A ready-to-use source code for the design of suggested filters is also provided.

Vessel target detection based on fusion range-Doppler image for dual-frequency high-frequency surface wave radar

Abstract: High-frequency surface wave radars (HFSWRs) have been used to monitor moving vessel targets within large areas of the coastal ocean. Moreover, a dual-frequency HFSWR can overcome the negative effect of sea clutter on vessel target detection. As only the information of point targets are used in the traditional point association method of dual-frequency HFSWR, it is difficult to select proper threshold values to obtain correct association and fusion results, which will increase the false alarm or miss rate. In this study, it is found that a moving vessel target is shown as an area target rather than a point target in range-Doppler (R-D) image. First, from the characteristic analyses of a vessel target in R-D fusion image, it is concluded that the two constant false alarm rate points of a single vessel target should locate within the same area target in the fusion image when it is detected by both frequencies. Then a new detection method of dual-frequency HFSWR was proposed on a fusion R-D image level. Finally, the proposed method is validated with the measured HFSWR data, and the results show that it can obtain more reliable association results than the traditional point association method.

Invariant subspace detector in distributed multiple-input multiple output radar: geometry gain helps improving moving target detection

Abstract: To detect moving targets in a distributed multiple-input multiple output (MIMO) radars, it is preferable to null the clutter rather than whiten the clutter This is mainly because clutter nulling approaches do not require range training data to form a sample covariance estimate of clutter in each transmit-receive pair, especially in the distributed MIMO radars with non-homogeneous clutter Moreover, geometry diversity of the distributed MIMO helps improve moving target detection since for a given target velocity, different transmit-receive pairs produce different Doppler frequencies that are less likely to be all small and reside in the clutter nulling region Based on these facts, the authors consider a subspace model for clutter and derive a uniformly most powerful invariant (UMPI) detector as an optimum invariant test In this case, analytical expressions for calculating the false alarm and detection probabilities for Swerling 0 and Swerling 1 target models are derived in the closed-forms Moreover, theoretical and numerical analyses of the proposed UMPI test are represented for several scenarios More importantly, the simulation results show that the proposed subspace-based UMPI detector can attain the predetermined false alarm probability and superior detection performance in the presence of correlated clutter Finally, authors consider a situation in which perfect waveform separations at the local receivers are no longer valid, and see the detection performance degradation of the proposed optimal detector designed for ideal waveform separations