Showing papers on "Moving target indication published in 2014"
TL;DR: The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.
Abstract: In order to effectively detect moving targets in heavy sea clutter, the micro-Doppler (m-D) effect is studied and an effective algorithm based on short-time fractional Fourier transform (STFRFT) is proposed for target detection and m-D signal extraction. Firstly, the mathematical model of target with micromotion at sea, including translation and rotation movement, is established, which can be approximated as the sum of linear-frequency-modulated signals within a short time. Then, due to the high-power, time-varying, and target-like properties of sea spikes, which may result in poor detection performance, sea spikes are identified and eliminated before target detection to improve signal-to-clutter ratio (SCR). By taking the absolute amplitude of signals in the best STFRFT domain (STFRFD) as the test statistic, and comparing it with the threshold determined by a constant false alarm rate detector, micromotion target can be declared or not. STFRFT with Gaussian window is employed to provide time-frequency distribution of m-D signals, and the instantaneous frequency of each component can be extracted and estimated precisely by STFRFD filtering. In the end, datasets from the intelligent pixel processing radar with HH and VV polarizations are used to verify the validity of this proposed algorithm. Two shore-based experiments are also conducted using an X-band sea search radar and an S-band sea surveillance radar, respectively. The results demonstrate that the proposed method not only achieves high detection probability in a low-SCR environment but also outperforms the short-time Fourier transform-based method.
147 citations
TL;DR: This paper recast detection of sea-surface floating small targets as a one-class anomaly detection problem in the 3D feature space, and proposes a tri-feature-based detector that attains better detection performance than several existing detectors.
Abstract: It is always a challenging problem for marine surface surveillance radar to detect sea-surface floating small targets. Conventional detectors using incoherent integration and adaptive clutter suppression have low detection probabilities for such targets with weak returns and unobservable Doppler shifts. In this paper, three features of a received vector at a resolution cell-the relative amplitude, relative Doppler peak height, and relative entropy of the Doppler amplitude spectrum-are exploited to give returns with targets from sea clutter. Real datasets show that each feature alone has some discriminability, and the three features jointly exhibit strong discriminability. Due to diversity of targets in practice, it is impossible to get features of returns with all kinds of targets. We recast detection of sea-surface floating small targets as a one-class anomaly detection problem in the 3D feature space. A fast convexhull learning algorithm is proposed to learn the decision region of the clutter pattern from feature vectors of clutter-only observations. As a result, a tri-feature-based detector is developed. The experiment results for the IPIX datasets show that the proposed detector at an observation time of several seconds attains better detection performance than several existing detectors.
91 citations
TL;DR: By estimating and compensating for the third-order phase error, the imaging resolution of the fast-moving target is improved and the motion parameters, including the cross-track acceleration, are correctly estimated.
Abstract: This letter proposes a novel algorithm for focusing moving targets with fast cross-track velocities and estimating their motion parameters with single-antenna synthetic aperture radar. The spectrum of a fast-moving target contains the Doppler ambiguity and the third-order phase error. Hough transform is utilized to estimate the slope of the range walk trajectory, from which the cross-track velocity is obtained and the Doppler ambiguity problem is solved. Then, polynomial Fourier transform is adopted to estimate the second- and third-order Doppler parameters of the moving target. By estimating and compensating for the third-order phase error, the imaging resolution of the fast-moving target is improved and the motion parameters, including the cross-track acceleration, are correctly estimated. Both simulated and real data processing results are provided to demonstrate the effectiveness of the proposed algorithm.
83 citations
24 Aug 2014
TL;DR: This work proposes classes of novel trajectory outlier definitions that model the anomalous behavior of moving objects for a large range of real time applications and proposes a general strategy for efficiently detecting the new outlier classes.
Abstract: The detection of abnormal moving objects over high-volume trajectory streams is critical for real time applications ranging from military surveillance to transportation management. Yet this problem remains largely unexplored. In this work, we first propose classes of novel trajectory outlier definitions that model the anomalous behavior of moving objects for a large range of real time applications. Our theoretical analysis and empirical study on the Beijing Taxi and GMTI (Ground Moving Target Indicator) datasets demonstrate its effectiveness in capturing abnormal moving objects. Furthermore we propose a general strategy for efficiently detecting the new outlier classes. It features three fundamental optimization principles designed to minimize the detection costs. Our comprehensive experimental studies demonstrate that our proposed strategy drives the detection costs 100-fold down into practical realm for applications producing high volume trajectory streams to utilize.
61 citations
TL;DR: Using UHF-band SAR ground moving target indication (GMTI) for suppressing forest and increasing the target signal can work, and the gain obtained can be measured using signal-to-clutter-and-noise-ratio gain, which is about 19 dB.
Abstract: In this paper, the results of moving-target detection in multichannel UHF-band synthetic aperture radar (SAR) data are shown. The clutter suppression is done using finite-impulse response (FIR) filtering of multichannel SAR in combination with a two-stage fast-backprojection algorithm to focus the moving target using relative speed. The FIR filter coefficients are chosen with the use of space-time adaptive processing filtering. Two parameters are used for target focusing, target speed in range and in azimuth. When the target is focused, both speed parameters of the target are found. In the experimental results, two channels were used in order to suppress clutter. In the resulting SAR images, it is obvious that very strong scatterers and the forest areas have been suppressed in comparison to the moving target in the image scene. The gain obtained can be measured using signal-to-clutter-and-noise-ratio gain, which is about 19 dB. Another way to measure the signal processing gain is the ability to suppress the strongest reflecting object in the SAR scene. The gain of the target in relation to this object is 25 dB. This shows that using UHF-band SAR ground moving target indication (GMTI) for suppressing forest and increasing the target signal can work.
43 citations
TL;DR: This work studies the problem of pulsed-radar transmit code design for detection of moving targets in the presence of signal-dependent clutter and proposes several algorithms under two novel frameworks to solve highly nonconvex design problems.
Abstract: In this paper, we study the problem of pulsed-radar transmit code design for detection of moving targets in the presence of signal-dependent clutter. For unknown target Doppler shift, the optimal d ...
40 citations
TL;DR: This chapter covers signal processing algorithms that proved valuable in allowing proper imaging and image recovery in the presence of high clutter, caused by front walls, and multipath, cause by reflections from internal walls, in Through-the-Wall radar imaging.
Abstract: Through-the-Wall radar imaging (TWRI) is emerging as a viable technology for providing high quality imagery of enclosed structures. TWRI makes use of electromagnetic waves below the S-band to penetrate through building wall materials. The indoor scene can be illuminated from each antenna, and be reconstructed using the data from the receive antennas. Due to the “see”-through ability, TWRI has attracted much attention in the last decade with a variety of important civilian and military applications. For instance, this technology is employed for surveillance and detection of humans and interior objects in urban environments, and for search and rescue operations in military situations. In this chapter, we cover signal processing algorithms that proved valuable in allowing proper imaging and image recovery in the presence of high clutter, caused by front walls, and multipath, caused by reflections from internal walls. Specifically, we focus on ground-based imaging systems which are relatively mature, and discuss wall mitigation techniques, multipath exploitation methods, change detection of moving target, and compressive sensing for fast data acquisition.
40 citations
TL;DR: This paper explains that there is a phase mismatch between azimuth channels for the echo of a moving target, which depends on range frequency, and an algorithm based on local maximum-likelihood minimum entropy is proposed to correct the PM.
Abstract: For high-resolution wide-swath (HRWS) SAR based on multiple receive apertures in azimuth, this paper proposes a novel imaging approach for moving targets. This approach utilizes the wide bandwidth characteristics of the transmitted signal (multiple wavelengths) to estimate the moving target velocity. First, this paper explains that there is a phase mismatch (PM) between azimuth channels for the echo of a moving target, which depends on range frequency. In order to correct the PM, an algorithm based on local maximum-likelihood minimum entropy is proposed. The linear dependence of the PM on range frequency is employed to estimate the target velocity. Second, after the signal reconstruction in Doppler frequency and the compensation of the PM for a moving target, the estimated target velocity is utilized to implement the linear range cell migration correction and the Doppler centroid shifting. Then, the quadratic range cell migration is corrected by the keystone processing. After that, the focused moving target image can be obtained using the existing azimuth focusing approaches. Theoretical analysis shows that no interpolation is needed. The effectiveness of the imaging algorithm for moving targets is demonstrated via simulated and real measured ship HRWS ScanSAR data.
30 citations
TL;DR: This letter proposes a novel deramp space-time adaptive processing (Deramp-STAP) method for synthetic aperture radar (SAR) systems to achieve effective clutter suppression and can overcome the spectral wrapping problem of a moving target from a Doppler shift.
Abstract: This letter proposes a novel deramp space-time adaptive processing (Deramp-STAP) method for synthetic aperture radar (SAR) systems to achieve effective clutter suppression. Compared with the traditional STAP, the proposed method can overcome the spectral wrapping problem of a moving target from a Doppler shift. Furthermore, in the case of signal undersampling, the ambiguously focused position in azimuth for a moving target can be avoided by the proposed method. Moreover, the computational complexity can be drastically reduced because we only need to consider the baseband velocity of the moving target; here, the range of the baseband velocity is much smaller than that of the real target velocity, for clutter suppression in this method. Simulation results validate the effectiveness of the proposed algorithm.
29 citations
TL;DR: A more general formulation of SAR shadow dimensions and intensity for non-specific targets with an arbitrary motion is provided to provide insight as to the physical dimensions of a target.
Abstract: An occluded or dark region in synthetic aperture radar (SAR) imagery, known as a shadow, is created when incident radar energy is obstructed by a target with height from illuminating resolution cells immediately behind the target in the ground plane. Shadows depend on the physical dimensions and mobility of a target, platform and radar imaging parameters, and scene clutter. Target shadow dimensions and intensity can be important radar observables in SAR imagery for target detection, location, and tracking or even identification. Stationary target shadows can provide insight as to the physical dimensions of a target, while moving target shadows may show more accurately the location and motion of the target over time versus Doppler energy which may be shifted or smeared outside the scene. However, SAR shadows prove difficult to capture as a target or platform moves, since the quality of the no-return area may quickly be washed-out in a scene over many clutter resolution cells during an aperture. Prior work in the literature has been limited to describing partial shadow degradation effects from platform or target motion of vehicles such as static target shadow tip or interior degradation during an aperture, or shadow degradation due to target motion solely in cross-range. In this paper, we provide a more general formulation of SAR shadow dimensions and intensity for non-specific targets with an arbitrary motion.
25 citations
TL;DR: This work generalizes the PHAF to handle two-dimensional PPS's and shows an example of application motivating such an extension: the high resolution imaging of moving targets from synthetic aperture radars (SAR).
Abstract: Polynomial-phase signals (PPS) appear in a variety of applications and several algorithms are available to estimate their parameters in the presence of noise. Among the available tools, the product high order ambiguity function (PHAF) has the merit of performing well in the presence of a superposition of PPS's. In this work, we generalize the PHAF to handle two-dimensional PPS's. Then we show an example of application motivating such an extension: the high resolution imaging of moving targets from synthetic aperture radars (SAR). Using the 2D-PHAF, we will propose an algorithm that compensates jointly for the range cell migration and the phase modulation induced by the relative radar-target motion in order to produce a focused image of the moving target. Numerical results illustrate the advantages of the proposed method when compared to existing auto-focusing algorithms.
TL;DR: This work investigates the Doppler blind zone in the case of bistatic transmitter and receiver configurations and its impact on the tracking of ground targets, and incorporates it into a Bayesian unscented Kalman filter multiple hypothesis tracker (UKF-MHT) tracking filter that is also capable of using road-map information.
Abstract: One of the main challenges in the domain of ground target tracking based on measurements from airborne ground moving target indication (GMTI) radar is the masking of targets due to the Doppler blind zone of the sensor. This blind zone arises from the clutter cancellation by space-time adaptive processing (STAP) to separate moving target returns from the general clutter background. Low-Doppler targets can easily be masked by such a blind zone, leading to sequences of missed detections that strongly deteriorate the performance of a standard tracking filter. This work investigates the Doppler blind zone in the case of bistatic transmitter and receiver configurations and its impact on the tracking of ground targets. The knowledge on the Doppler blind zone is incorporated into a Bayesian unscented Kalman filter multiple hypothesis tracker (UKF-MHT) tracking filter that is also capable of using road-map information. Based on different simulation scenarios, it is demonstrated that in contrast to a monostatic configuration with sideways-looking radar, the blind zone width determined by the minimum detectable velocity is not constant in general. The obtained track results reveal the benefit of exploiting this additional knowledge, especially in combination complementary with road-map information if available.
TL;DR: In this paper, the use of along-track interferometry (ATI) and the displaced phase center antenna (DPCA) is extended to detect and geo-locate all observable moving targets in the Gotcha challenge data, including both the scripted movers and targets of opportunity.
Abstract: In previous work, we presented GMTI detection and geo-location results from the AFRL Gotcha challenge data set, which was collected using a 3-channel, X-band, circular SAR system. These results were compared against GPS truth for a scripted vehicle target. The algorithm used for this analysis is known as ATI/DPCA, which is a hybrid of along-track interferometry (ATI) and the displaced phase center antenna (DPCA) technique. In the present paper the use of ATI/DPCA is extended in order to detect and geo-locate all observable moving targets in the Gotcha challenge data, including both the scripted movers and targets of opportunity. In addition, a computationally efficient SAR imaging technique is presented, appropriate for short integration times, which is used for computing an image of the scene of interest using the same pulses of data used for the GMTI processing. The GMTI detections are then overlaid on the SAR image to produce a simultaneous SAR/GMTI map.
TL;DR: It is shown that the proposed algorithm significantly reduces imaging artifacts while preserving the moving target signature.
Abstract: A moving target indication, noncoherent change detection algorithm is introduced to detect moving targets inside buildings. The proposed algorithm is designed to attenuate image artifacts observed in coherent change detection images by utilizing noncoherent change detection, a positive threshold operation, and sidelobe minimization. The proposed algorithm is compared with coherent change detection for three moving target scenarios. It is shown that the proposed algorithm significantly reduces imaging artifacts while preserving the moving target signature.
TL;DR: Experimental results from SAR-GMTI data validate the effectiveness of the newly proposed baseline estimation method, which is designed to account for the variation of interferometric phase variance over different Doppler bins.
Abstract: For multichannel synthetic aperture radar based ground moving-target indication (SAR-GMTI), the effective baseline usually needs to be estimated in order to obtain an accurate estimate of radial velocity for each moving target. This paper deals with the effects of Doppler aliasing on baseline estimation. We show that Doppler aliasing can introduce an interferometric phase uncertainty as well as an interferometric phase bias. The phase uncertainty will increase the variance of the baseline estimate, whereas the phase bias will bias the baseline estimate. To address the aforementioned effects caused by Doppler aliasing, a new method for estimating the effective baseline is proposed. One of the key steps of this method is to perform an operation called sample censoring aimed at mitigating the problem of estimation bias. The censoring threshold can be approximately determined by introducing a concept referred to as equivalent variance for the interferometric phases of the entire Doppler bins. Moreover, in order to account for the variation of interferometric phase variance over different Doppler bins, a strategy of weighting is adopted. Experimental results from SAR-GMTI data validate the effectiveness of the newly proposed baseline estimation method.
TL;DR: A method called standardized maximum projection of temporal difference on adjacent frames (SMPTDAF) is proposed, and results show that the average SCR gain exceeds 11 when the target SCR is from 1.0 and 3, which is better than results of some representative multi-frame filters mentioned above.
TL;DR: The design considerations of PRF for optimizing GMTI performance in multichannel SAR systems with HRWS imaging capability are given, along with a simulation example to verify the theoretical investigations.
Abstract: Using multichannel in azimuth to suppress the Doppler ambiguities allows for high-resolution wide-swath (HRWS) synthetic aperture radar (SAR) imaging, thus overcoming the minimum antenna area constraint of the conventional space-borne SAR. If the degrees of freedom in azimuth are used for the clutter suppression, the ground moving target indication (GMTI) can be achieved. Therefore, a space-borne multichannel SAR system for GMTI has the potential to offer HRWS imaging capability to some extent. However, here, the GMTI performance may suffer from the Doppler ambiguity caused by the undersampling. This paper focuses on the analysis of the influence of pulse repetition frequency (PRF) on GMTI performance in Doppler ambiguity. The multichannel signal models of the clutter and the moving target with Doppler ambiguity are derived in complex image domain. Considering the Doppler ambiguity and the multichannel spatial ambiguity, the influence of PRF on the output signal-to-clutter-plus-noise ratio after adaptive clutter suppression and the signal-to-noise ratio loss after SAR imaging is discussed. Accordingly, the design considerations of PRF for optimizing GMTI performance in multichannel SAR systems with HRWS imaging capability are given, along with a simulation example. Finally, the real-data experiments verify the theoretical investigations.
TL;DR: A new approach is presented to detect ground moving targets and estimate their motion parameters for high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems and the spaceborne HRWS simulation data confirm the validity of the method.
Abstract: In this study, a new approach is presented to detect ground moving targets and estimate their motion parameters for high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems First, the space-time adaptive processing is adopted for clutter suppression, followed by the traditional SAR imaging and constant-false-alarm-rate detection for obtaining the ambiguous images of ground moving targets Then, the real targets can be distinguished from all the ambiguous ones based on the space relationship between ambiguous images Finally, according to the shift amount of moving targets in azimuth, which can be obtained by utilising the range histories of moving targets, the motion parameter can be achieved The spaceborne HRWS simulation data confirm the validity of the method
TL;DR: A two-antenna SAR with waveform diversity for GMTI is proposed, which cooperatively utilizes the advantages of ATI and DPCA GMTI techniques and overcomes their disadvantages.
Abstract: Along-track interferometry (ATI) and displaced phase center antenna (DPCA) are two representative synthetic aperture radar (SAR) ground moving target indication (GMTI) techniques. However, the former is a clutter-limited detector, whereas the latter is a noise-limited detector. In this letter, we propose a two-antenna SAR with waveform diversity for GMTI. The two antennas placed in the azimuth dimension simultaneously transmit two orthogonal waveforms, namely, the up- and down-chirp waveforms. In doing so, four independent transmit–receive channels are obtained for the receiver, and thus, an efficient GMTI is developed by cooperatively utilizing the ATI GMTI and DPCA GMTI processing techniques. This method first uses the DPCA technique to cancel clutter and then the ATI technique to suppress noise. Next, the fractional Fourier transform is employed to estimate the Doppler parameters and corresponding reference filters are designed to focus the moving targets. The proposed approach cooperatively utilizes the advantages of ATI and DPCA GMTI techniques and overcomes their disadvantages. It does not prerequire knowledge of the target's across-track velocity. The effectiveness is verified by simulation results.
04 Dec 2014
TL;DR: In this article, the authors proposed and assessed several clutter reduction techniques as pre-processing techniques to improve the signal-to-noise ratio, discriminate overlapping responses issued from the targets and the clutter, and ease the use of data processing algorithms for target detection, identification or reconstruction.
Abstract: A bi-static Ground Penetrating Radar (GPR) has been developed for the detection of cracks and buried pipes in urban grounds. It is made of two shielded Ultra Wide Band (UWB) bowtie-slot antennas operating in the frequency band [0.3;4] GHz. GPR signals contain not only responses of targets, but also unwanted effects from antenna coupling in air and in the soil, system ringing, and soil reflections that can mask the proper detection of useful information. Thus, it appears necessary to propose and assess several clutter reduction techniques as pre-processing techniques to improve the signal-to-noise ratio, discriminate overlapping responses issued from the targets and the clutter, and ease the use of data processing algorithms for target detection, identification or reconstruction. In this work, we have evaluated on Bscan profiles three different statistical data analysis such as mean subtraction, Principal Component Analysis (PCA), and Independent Component Analysis (ICA) considering a shallow and a medium depth target. The receiver operating characteristics (ROC) graph has allowed to evaluate the performance of each data processing in simulations and measurements to further draw a comparison in order to select the technique most adapted to a given soil structure with its radar probing system.
TL;DR: The actual chapter provides a comprehensive tutorial for GMTI with SAR systems and the basic moving target detection and parameter estimation techniques used in state-of-the-art multi-channel algorithms are treated.
Abstract: Modern multi-channel air- and spaceborne synthetic aperture radar (SAR) sensors allow for a variety of applications, independent of sunlight illumination and weather conditions. One application is ground moving target indication (GMTI) with the aim to detect moving targets on ground and to estimate their positions, velocities and moving directions. Although originated in the military field, nowadays GMTI also has gained relevance for civilian road traffic monitoring to ensure the mobility and to increase the safety of the road users. The actual chapter provides a comprehensive tutorial for GMTI with SAR systems. The effects on SAR imagery caused by moving targets are addressed in detail. Additionally, the basic moving target detection and parameter estimation techniques used in state-of-the-art multi-channel algorithms are treated. Finally an outlook to future trends is given.
06 Jul 2014
TL;DR: This paper addresses the tracking of moving targets using a stepped frequency linear antenna array is addressed through the compressive sensing (CS) framework using the Orthogonal Matching Pursuit (OMP) algorithm to reconstruct the target space using measurements at a small number of randomly selected frequencies.
Abstract: In this paper, the tracking of moving targets using a stepped frequency linear antenna array is addressed through the compressive sensing (CS) framework. Multiple targets are resolved in the three-dimensional directions of arrival (DoA)-range-Doppler space for each time instant. The Orthogonal Matching Pursuit (OMP) algorithm is utilized to reconstruct the target space using measurements at a small number of randomly selected frequencies. The performance of the proposed approach is evaluated through simulation result in terms of accuracy and computational complexity.
TL;DR: The authors presented a mathematical framework for processing multichannel SAR data in order to mitigate the combined effects of moving target defocus and strong clutter interference and presented the potential improvements to SINR loss using the adaptive processing compared to more standard STAP approaches.
Abstract: The authors have defined an approach for detecting and tracking moving vehicles with Gotcha radar systems. Our approach exploits tracker feedback to address challenges for detection, false alarm mitigation, geolocation, and tracking in an urban surveillance environment. The authors presented a mathematical framework for processing multichannel SAR data in order to mitigate the combined effects of moving target defocus and strong clutter interference. The algorithm uses MRP adaptively in a STAP framework to focus up moving vehicles and enhance signal to clutter ratios. Using simulated data, we illustrated SAR defocus of an accelerating point scatterer and mitigation of the defocus using MRP. For this simulated example, we also presented the potential improvements to SINR loss using our adaptive processing compared to more standard STAP approaches.
TL;DR: Measurements from a realistic scene using a radar system operating at X-band in a stepped-frequency mode shows that two persons moving in the scene can be separated, when allowed by the range resolution.
Abstract: The possibility of detecting moving people around the corner using multipath propagation of radar waves has previous been demonstrated in experimental set-ups. Here, we present measurements from a realistic scene using a radar system operating at X-band in a stepped-frequency mode. The moving objects include person(s), bicycle, and car(s). A semi-monostatic single receiver-transmitter radar system was used as a data collector. All detections were made by using Doppler filter processing.
We can identify target returns after one and two wall reflections. Two persons moving in the scene can be separated, when allowed by the range resolution.
TL;DR: An approach for ambiguity-free motion parameter estimation of ground moving targets with arbitrary velocity and constant acceleration from dual-channel synthetic aperture radar (SAR) sensors is proposed and the nth-order keystone transform is used to mitigate the range migration induced by the target's residual motion after the ambiguity removal.
Abstract: In this paper, we propose an approach for ambiguity-free motion parameter estimation of ground moving targets with arbitrary velocity and constant acceleration from dual-channel synthetic aperture radar (SAR) sensors. For targets with high and low signal-to-clutter-noise ratios (SCNRs), different analytic expressions for along/cross-track velocities and accelerations estimation are derived, respectively. The ambiguities induced by the motion parameters in practical applications are analyzed in detail and appropriate solutions are proposed. We use the nth-order keystone transform to mitigate the range migration induced by the target's residual motion after the ambiguity removal. The effectiveness of the proposed algorithm is verified by processing both simulated and measured stripmap SAR data.
19 May 2014
TL;DR: It is shown that Keystone transform based approach outperforms the conventional approach in terms of better Doppler resolution and less range-Doppler image blurring.
Abstract: The feasibility of using Keystone transform based range migration compensation for range-Doppler processing in ultra-wideband (UWB) moving target indication (MTI) radar is investigated. The conventional Fourier transform based approach is outlined, and the challenge of using the conventional method in UWB radar for slow-moving extended target (human) is addressed. Keystone transform is applied to both simulated and experimental human target data. It is shown that Keystone transform based approach outperforms the conventional approach in terms of better Doppler resolution and less range-Doppler image blurring. The result also demonstrates that hypothesis-testing based approach and Keystone Transform based approach have similar performance, but the latter is more suitable for real-time implementation due to its smaller computation burden.
04 May 2014
TL;DR: An adaptive waveform scheduling algorithm is presented for target tracking by a multistatic radar system with two key components: a distributed multistatics tracking algorithm for targettracking in cluttered environments, and the next transmitted waveform selected to minimize the tracking mean squared error.
Abstract: An adaptive waveform scheduling algorithm is presented for target tracking by a multistatic radar system with two key components: (i) a distributed multistatic tracking algorithm for target tracking in cluttered environments, and (ii) the next transmitted waveform selected to minimize the tracking mean squared error. The scheduling algorithm is developed based on the minimization of the trace of the expected tracking error covariance matrix. A simulation example is presented to demonstrate the superiority of the proposed waveform scheduling algorithm over conventional fixed waveforms.
01 Jan 2014
TL;DR: Whether motion modeling and characterization is performed or change detection is applied, it is shown that the targets, maintaining or migrating their range, can be localized with significantly reduced amount of data due to sparseness in space and velocity.
Abstract: This chapter considers sparsity-driven moving target indication. A radar imaging system can recognize an animate target indoors by a change in target position. The course of that change can be continuously or nonconsecutively monitored by the radar. The target location over time can be guided by a particular model or characterized by a specific motion profile. In this case, using a sequence of radar pulses, target velocity and its derivatives, including acceleration, can be obtained by estimating the corresponding Doppler frequency and higher-order motion parameters. Alternatively, the radar may illuminate the scene at particular time instants to capture the target at different positions. Detection of target position variations by subtraction of data or images at different time instants is the foundation of change detection where details of motion profile 251 © 2015 by Taylor & Francis Group, LLC 252 Compressive Sensing for Urban Radar are difficult to discern and become irrelevant to motion indication. These instants can be widely separated, several pulses apart, or consecutive to detect short human movements. Whether motion modeling and characterization is performed or change detection is applied, we show in this chapter that the targets, maintaining or migrating their range, can be localized with significantly reduced amount of data due to sparseness in space and velocity. 8.
TL;DR: A new method of effective baseline estimation is presented, which can be used for ground moving target indication (GMTI) mode of synthetic aperture radar (SAR) and shows that the incorporation of the fine co-registration and the median filtering procedures in the estimation scheme represents an accurate solution to theeffective baseline estimation problem.
Abstract: In this study, a new method of effective baseline estimation is presented, which can be used for ground moving target indication (GMTI) mode of synthetic aperture radar (SAR).The basic idea is to perform the baseline estimation via exploiting the slope of the along-track interferometric (ATI) phase ramp in two-dimensional frequency domain. An integrated scheme of effective ATI-baseline estimation is proposed, which includes two key procedures: fine co-registration and median filtering. The proposed algorithm is tested with real SAR data. The results show that the incorporation of the fine co-registration and the median filtering procedures in the estimation scheme represents an accurate solution to the effective baseline estimation problem.
13 Jul 2014
TL;DR: An automatic DPCA technique is presented for SAR Ground Moving Target Indication (GMTI) that can be implemented in the following steps: Image registration, phase compensation, image subtraction, and CFAR detection.
Abstract: An automatic DPCA technique is presented for SAR Ground Moving Target Indication (GMTI). We note that there exists a shift and a phase difference between the images from two channels. Therefore, SAR-GMTI can be implemented in the following steps: Image registration, phase compensation, image subtraction, and CFAR detection. In our technique, these steps are carried out automatically, and thus no precise information is needed about the length of the baseline and the velocity of the platform. We utilize a set of real data to demonstrate the accuracy and the robustness of our algorithm.