Ground Moving Target Indication Radar Research Articles

Application of Digital Twin Technology in Synthetic Aperture Radar Ground Moving Target Intelligent Detection System

In recent years, the detection performance of SAR-GMTI (synthetic aperture radar-ground moving target indication) algorithm based on deep learning has always been limited by insufficient measured data due to the heavy operation complexity and high cost of real SAR systems. To solve this problem, this paper proposes an overall DT-based implementation framework for SAR ground moving target intelligent detection tasks. In particular, by virtue of a SAR imaging algorithm, a high-fidelity twin replica of SAR moving targets is established in digital space through parameter traversal based on the prior target characteristics of the obtained measured datasets. Then, the constructed SAR twin datasets is fed into the neural network model to train an intelligent detector by fully learning features of the moving targets and preset the SAR scene in the twin space, which can realize the robust detection of ground moving targets in related practical scenarios with no need for multiple and complex field experiments. Moreover, the effectiveness of the proposed framework is verified on the MiniSAR measured system, and a comparison with traditional CFAR detection method is given simultaneously.

Moving Targets Detection for Video SAR Surveillance Using Multilevel Attention Network Based on Shallow Feature Module

In this article, a novel method for the moving target detection through multilevel spatial and channelwise attention network based on shallow feature channel module (MSCA-SFCM) is presented, and the circular spotlight (CSL) video synthetic aperture radar ground moving target indication (Video-SAR-GMTI) mode of the Nanjing University of Aeronautics and Astronautics miniature SAR (NUAA MiniSAR) system is introduced. However, due to the lack of moving target samples, MSCA-SFCM cannot be directly applied to the CSL Video-SAR-GMTI mode in the real system. To this end, this article proposes a training sample library construction scheme for moving targets of high verisimilitude. In this scheme, based on the radar system parameters, after the traversal of moving target parameters and SAR imaging, the scattering line characteristic of all possible moving targets under the current system parameters is simulated and then used for MSCA-SFCM network training. Afterward, the properly trained network can be used for moving target detection in real radar data. The effectiveness of the proposed method is verified by the NUAA MiniSAR system.

Ground Moving Target Detection and Trajectory Reconstruction Methods for Multichannel Airborne Circular SAR

Synthetic aperture radar ground moving target indication (SAR-GMTI) is an attractive mode for radar system to obtain high-resolution regional images and detection of moving targets simultaneously. Moreover, the 360° observation capability of circular SAR (CSAR) makes it possible for moving target trajectory reconstruction. In order to address the problem that slow-moving targets, which are buried in strong stationary ground clutter, are difficult to be detected, a framework of multichannel SAR-GMTI is presented in this article. For ground moving target detection in the presence of stationary clutter, the proposed method first adopts clutter suppression interferometry and relaxation-based cyclic algorithm to suppress clutterand retrieve parameters (e.g., radial velocity and Doppler information). Then, to further reduce the false alarm rate, multiple moving target tracking algorithm is performed in range–Doppler domain. Finally, the moving target trajectory is reconstructed by using the proposed two-stage parameter estimation method based on Doppler characteristic and CSAR geometry, and the mathematical analysis of this method is performed. The proposed method is robust and insensitive to the signal-to-noise ratio. It does not rely on priori road information, so it has wide applicability, especially in military application. In addition, the framework is performed in echo domain and independent of imaging processing. The experimental results on simulated data are presented to evaluate the estimation accuracy of the proposed method, and the real data processing results are provided to demonstrate the validity and feasibility of the proposed method.

A SAR‐GMTI method based on changes of polarization characteristics before and after clutter suppression

Due to the azimuth shift and defocus of the moving targets in the synthetic aperture radar image domain, a new synthetic aperture radar ground moving target indication method is proposed in this letter based on the changes of moving targets’ polarization characteristics before and after clutter suppression. This method can effectively suppress the false alarms caused by the man-made objects compared with the displaced phase centre array method in the complex scenes. Finally, the effectiveness of the proposed method is verified by the real multi-channel quadrature-polarimetric synthetic aperture radar data.

Range Ambiguous Clutter Suppression Approach With Elevation Time Diverse Array

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

Frequency Diverse Array Introduced Into SAR GMTI to Mitigate Blind Velocity and Doppler Ambiguity

In this letter, a frequency diverse array (FDA) is introduced into synthetic aperture radar ground moving target indication (SAR GMTI) to mitigate both the blind velocity and Doppler ambiguity problems. Due to the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula> periodicity of the echo phases, notches will occur periodically in clutter cancelers at nonzero velocities, leading to the blind velocity problem. In the proposed scheme, the dependence of the measured blind velocity on the transmission frequency is considered, and a new clutter canceler unaffected by the blind velocity problem is constructed via the integration of multiple cancelers with diverse frequencies. Moreover, to resolve the Doppler ambiguity, along-track interferometry (ATI) based double interferometry is proposed to extend the maximum unambiguous radial velocity (RV). Additionally, search-based clustering is adopted to enhance the precision of RV estimation. Finally, a moving target can be brought into focus and correctly relocated using the estimated RV. Numerical results verify the effectiveness of the proposed method.

Bistatic SAR Clutter-Ridge Matched STAP Method for Nonstationary Clutter Suppression

Clutter suppression is a challenging task in synthetic aperture radar-ground moving target indication (SAR-GMTI). In general, sufficient secondary samples are not easily acquired due to the nonstationary and nonhomogeneous characteristics of bistatic SAR (BiSAR) clutter, resulting in worse clutter suppression results. Recently, space–time adaptive processing based on sparse recovery (SR-STAP) has been developed since its better clutter suppression performance with less samples. However, since the off-grid problem in space–time domain caused by BiSAR’s separate configuration, existing SR-STAP would suffer from severe performance degradation. To address this problem, a clutter-ridge matched STAP (CRM-STAP) method for BiSAR nonstationary clutter suppression is proposed. First, clutter distribution modeling with arbitrary BiSAR configuration is applied to accurately obtain the clutter ridge in space–time domain. Then, keystone transform and time-division processing are applied to correct range cell migration and eliminate Doppler frequency migration, respectively. Next, to solve the off-grid problem, the CRM dictionary is reconstructed via adaptive gradient method, which is established along the direction of clutter ridge and its orthogonal direction. Then, with the constructed CRM dictionary, the clutter covariance matrix (CCM) estimation process is transformed to a multimeasured vector optimization problem, and it can be directly solved by the sparse Bayesian learning algorithm. Finally, based on the estimated CCM, the CRM-STAP filter is built to suppress the nonstationary clutter effectively. Compared with the existing STAP and SR-STAP methods, this method can avoid the performance degradation in clutter suppression caused by the off-grid problem and overcomes the strong nonstationary problem of BiSAR clutter in heterogeneous environments. In October 2020, we have successfully carried out the world’s first airborne BiSAR-GMTI experiment, and the experimental results are given to verify the effectiveness of this method.

An Improved Scattered Wave Deceptive Jamming Method Based on a Moving Jammer Beam Footprint Against a Three-Channel Short-Time SAR GMTI

To effectively generate a verisimilar false moving target against a three-channel synthetic aperture radar ground moving target indication (SAR GMTI), a scattered wave deceptive jamming method performed by the time-delay modulation and the phase modulation (STP) is first proposed by using traditional deceptive jamming strategies. In addition, a novel three-channel short-time SAR GMTI method (TCSTSG) is heuristically inspired by the short-time Fourier transform (STFT) method and proposed with anti-jamming capacity. The procedure of the TCSTSG method is to divide the whole-time data into shorter segments, and each segment will be processed by displaced phase center antenna (DPCA) technique and along-track interferometry (ATI) technique. With the TCSTSG method, the moving target will have different positions in each segment. However, the false target generated by the traditional deceptive jamming method based on multiple jammers (DJ-MJ) and the STP method has the same position in each segment and a verisimilar false moving target cannot be generated. To meet this challenge, an improved scattered wave deceptive jamming method based on the moving jammer beam footprint (SMJBF) is proposed. Compared with the traditional scattered wave jamming methods, the improvement is that the jammer can control the azimuth position and velocity of the footprint. The position and velocity are calculated by comparing the detection results of the moving target and those of the false target with the TCSTSG method. Then the false target will be similar to the moving target. Finally, simulations are provided to verify the effectiveness of the proposed methods.

A Multiple-Jammer Deceptive Jamming Method Based on Particle Swarm Optimization Against Three-Channel SAR GMTI

Traditional deceptive jamming methods effectively generate false targets against three-channel synthetic aperture radar ground moving target indication (SAR GMTI). However, effectiveness of traditional methods is limited to azimuth distance between two jammers. When the distance requirement is not satisfied, the jamming amplitude coefficients will be too high to be used by jammers. To overcome this disadvantage, a novel multiple-jammer deceptive jamming method is proposed. The intercepted radar signal is retransmitted and performed by amplitude and time-delay modulation. Then, jamming signal is first modeled as a polynomial function where the polynomial order is equal to the number of jammers. The interferometric phase difference between a moving target and a false target is utilized as an objective function, the azimuth relocated position difference between a moving target and a false target is utilized as the constraint to reduce computational burden, and the optimal jamming amplitude coefficients are estimated by solving the optimization problem based on the particle swarm optimization (PSO). Hereby, the optimal jamming amplitude coefficients and gain calculated with the proposed method will be lower than those calculated with traditional methods when the distance requirement is not satisfied. By utilizing the optimal coefficients and jamming amplitude gain, a false target generated with the proposed method will be detected by displaced phase center antenna (DPCA) technique and be relocated in the desired position by along-track interferometry (ATI) technique. Experimental results verify the effectiveness of the proposed method.

A Novel Two-Step Scheme Based on Joint GO-DPCA and Local STAP in Image Domain for Multichannel SAR-GMTI

Multichannel synthetic aperture radar ground moving target indication has been widely used and get great attention nowadays. Traditional adaptive methods like space-time adaptive processing (STAP) need to calculate and search the maximum of the test statistic pixel by pixel over a large range of radial velocity, which will cause great computational burden. Nonadaptive methods like displaced phase center antenna (DPCA) will cause signal loss of moving targets, thereby degrading the performance of moving targets detection and radial velocity estimation. To improve the problem mentioned above, this article proposes a novel two-step scheme based on greatest of (GO)-DPCA and Local STAP. In step I, GO-DPCA utilizes the complex images of the channels with different baselines for joint moving target detection. Then, in step II, only the local data of moving targets detected in step I needs to be extracted from the original image domain for clutter suppression and radial velocity estimation simultaneously by STAP. Since the processing gain of moving targets depends on the radial velocity and baseline length, the detection performance of moving targets with different radial velocity can be improved by proposed GO-DPCA compared to conventional DPCA. Considering the moving targets usually distribute sparsely in the scene, step II can avoid most computational burden caused by processing pixel by pixel. Finally, the experimental results of both simulated and acquired data are given to validate the effectiveness of the proposed method.

A Novel Moving Target Detection Method Based on RPCA for SAR Systems

Clutter background suppression and velocity estimation for moving targets are two critical problems in synthetic aperture radar-ground moving target indication (SAR-GMTI). A robust principal component analysis (RPCA) method is used to separate the sparse matrix of moving targets from the low-rank matrix of static backgrounds by using amplitude information in the image domain. However, the nonsparsity of the moving target echoes limits the performance of the RPCA in SAR-GMTI, and the velocity of the moving target cannot be estimated since the phase information is destroyed by the soft-thresholding operator in the RPCA process. To solve these problems, a novel moving target detection method based on RPCA (NRPCA) for SAR systems is proposed in this article. An atomic norm-based optimization program is first constructed to transform the data sparsity requirement into a moving target sparsity requirement. Although this optimization program is NP-hard, it is transformed to semidefinite programming by relaxation. Furthermore, accurate velocity estimation is performed using dual function theory and the alternating direction method of multipliers (ADMM) algorithm while the selection of the sparsity order k is avoided. Simulations and analyses based on experimental data illustrate the effectiveness of the proposed method.

A Clutter Suppression Method Based on NSS-RPCA in Heterogeneous Environments for SAR-GMTI

Clutter background suppression is a critical problem in synthetic aperture radar-ground moving target indication (SAR-GMTI). In general, a great quantity of secondary data is not easily acquired in heterogeneous environments. To solve the problem of clutter suppression, a method based on nonlocal self-similarity-robust principal component analysis (NSS-RPCA) is proposed for airborne SAR systems. First, discrete clutter is separated from the echo data by RPCA after range pulse compression. Second, similar blocks of the residual-clutter background are extracted to overcome the training sample limitation using the NSS method in the 2-D time domain. Third, subcovariance matrices are structured by the similar blocks, and the subcovariance matrix is stacked into a tensor. Then, the subclutter covariance matrix can be obtained from the stacked subcovariance matrix tensor by RPCA, where the residual-clutter tensor is of low rank and the target tensor is sparse. Finally, the residual clutter can be suppressed by the subclutter covariance matrix. In this manner, the source of independent identically distributed (IID) samples will be increased significantly without aperture loss by the proposed method. Simulation and analysis based on the experimental data illustrate the effectiveness of the proposed method.

An Interrupted Sampling Scattered Wave Deception Jamming Method against Three-Channel SAR GMTI

An important problem is how to generate false moving targets, whose relocated azimuth position is similar to that of real moving targets. To solve this problem, an interrupted sampling scattered wave deception jamming method against three-channel synthetic aperture radar ground moving target indication (SAR GMTI) is proposed. A stationary jammer uses a controllable jammer antenna to generate verisimilar moving targets by controlling velocity and initial position of jammer beam footprint. The antenna sampled moves along the different tracks. For each track, the slant history of jamming signal is changed varying with different pulse recurrence intervals (PRI), and the movement of the footprint will introduce a Doppler frequency in jamming the signal. By analyzing parameters’ difference between echoes and jamming signal, the velocity and the initial position of the footprint will be calculated, and then the verisimilar false targets are generated. The effectiveness of the method is verified by simulation experiments.

GMTI STAP performance under space‐time impaired clutter environment

Ground moving target indicator (GMTI) RADAR system frequently incorporates space-time adaptive processing for successful moving targets discrimination in a highly cluttered environment. The minimum detectable velocity (MDV) of the target gets affected due to the added clutter impairments such as foliage penetration and angle independent channel mismatch. A novel clutter model is postulated in this work that includes assessment enacted in view of both angle and Doppler clutter impairments at a time instead of their individual analysis as in the reported literature. The performance of the GMTI RADAR in terms of the signal-to-interference-plus-noise ratio loss is evaluated using the extrusive beamforming methods namely sample matrix inversion and principal component canceller. In high decorrelated clutter environment, the later outperforms in terms of the MDV, making use of a lesser number of training snapshots. The approach is validated with mathematical modelling and numerical simulations.

Deceptive jamming against multi‐channel SAR‐GMTI

Aimed at the problem that the deceptive jamming against synthetic aperture radar ground moving target indication generated by single jammer cannot work effectively in multi-channel SAR, a novel deceptive jamming against multi-channel SAR-GMTI based on two jammers is studied. First, signal model of the novel deceptive jamming is built. Then, based on three-channel clutter suppression and interferometry processing, the amplitude and interferometric phase of deceptive moving target generated by the novel deceptive jamming are derived. Last, simulation experiment validates that the novel deceptive jamming can generate false moving targets with the controllable radial velocity and located azimuth position in the multi-channel SAR.

A Robust Radial Velocity Estimation Method for FDA-SAR

In multi-channel synthetic aperture radar-ground moving target indication (SAR-GMTI), most radial velocity estimation methods are based on the phase difference between channels. However, the image coregistration and channel phase errors will have a severe impact on the phase difference between channels. Moreover, it deteriorates the performance of the moving target radial velocity estimation. To solve this problem, a robust radial velocity estimation method is proposed using a frequency diverse array-SAR (FDA-SAR) in this letter. By introducing the step frequency, the interferometric phase among channels is a linear function of the Doppler frequency. The radial velocity of moving targets is embedded in the first-order term of the linear function. Meanwhile, the first-order term does not include channel phase error terms. Therefore, the accurate velocity of moving targets is estimated by the first-order coefficient which is solved by the least-squares fitting method. Afterward, according to the analysis and derivation, the proposed method is robust on the condition of image coregistration error. At last, simulations and data analysis illustrate the effectiveness of the proposed method.

Syntactic Enhancement to VSIMM for Roadmap Based Anomalous Trajectory Detection: A Natural Language Processing Approach

Syntactic tracking aims to classify a target's spatio-temporal trajectory by using natural language processing models. This paper proposes constrained stochastic context-free grammar (CSCFG) models for target trajectories confined to a roadmap. We present a particle filtering algorithm that exploits the CSCFG model structure to estimate the target's trajectory. This metalevel algorithm operates in conjunction with a base-level target tracking algorithm. Extensive numerical results using simulated ground moving target indicator radar measurements show useful improvement in both trajectory classification and target state (both coordinates and velocity) estimation.

General Signal Model for Multiple-Input Multiple-Output GMTI Radar.

Multiple-input multiple-output (MIMO) ground moving target indication (GMTI) radar has been studied recently because of its excellent performance. In this paper, a general signal model is established for the MIMO GMTI radar with both fast-time and slow-time waveforms. The general signal model can be used to evaluate the performance of the MIMO GMTI radar with arbitrary waveforms such as the ideal orthogonal, code division multiple access (CDMA), frequency-division multiple access (FDMA), time division multiple access (TDMA), and Doppler division multiple access (DDMA) waveforms. We proposed a range-compensation method to eliminate the range-dependence of the FDMA waveforms. The simulation results indicate that the improved performance of FDMA waveforms is achieved utilizing the range-compensation method.

A new Gaussian mixture method with exactly exploiting the negative information for GMTI radar tracking in a low-observable environment

This paper investigates the problem of ground vehicle tracking with a 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 when it stops, i.e. falling into the Doppler blind region. Besides, there will be false alarms in low-observable environments where there exist high noises interferences. In this paper, we develop a novel algorithm for the GMTI tracking in a low-observable environment with false alarms while exactly incorporating the ‘negative information’ (i.e., the target is likely to stop when no measurements are recorded) based on the Bayesian inference framework. For the Bayesian inference implementation, the Gaussian mixture approximation method is adopted to approximate related distributions, while different filtering algorithms (including both extended Kalman filter and its generalization for interval-censored measurements) are applied for updating the Gaussian mixture components. Target state estimation can be directly obtained through the Gaussian mixture model for the GMTI tracking at every time instance. We have compared the developed method with other state-of-the-art ones and the simulation results show that the proposed method substantially outperforms the existing methods for the GMTI tracking problem.

Blind velocities mitigation for MIMO GMTI radar with Doppler division multiple access waveforms

Multiple-input multiple-output (MIMO) radar with multiple transmitters and multiple receivers can achieve a larger virtual antenna array and more system degrees of freedom; thus applying it to ground moving target indication (GMTI) radar can improve the performance of GMTI. Doppler division multiple access (DDMA) waveforms are approximately orthogonal providing good minimum detectable velocity (MDV) performance. However, in such DDMA systems, a sufficient pulse repetition frequency (PRF) design freedom is required. Furthermore, these waveforms suffer from blind velocities which are serious problems, especially in radar systems with high carrier frequency or low PRF. This paper analyses the blind velocities problem and show that blind velocities are relative to variation of the PRF and/or the carrier frequency. Variable PRF techniques are widely used in conventional GMTI radar including multiple PRFs and variable pulse repetition intervals (PRI). Combined with the characteristics of the DDMA MIMO GMTI radar, this paper proposed two methods to mitigate blind velocities: “multi-PRF DDMA” which employs multiple PRFs over successive coherent processing intervals, and “PRI-dithered DDMA” which employs nonuniform sampling by dithered PRI in slow time. Simulation results demonstrate that both the methods are effective ways to mitigate blind velocities in DDMA MIMO GMTI radar systems.