Target location with signal fitting and sub-aperture tracking for airborne multi-channel radar

The location of a moving target based on signal fitting and sub-aperture tracking from an airborne multi-channel radar is dealt with.The proposed approach is applied in two steps：first,the ambiguous slant-range velocity is derived with a modified single-snapshot multiple direction of arrival estimation method,and second,the unambiguous slant-range velocity is found using a track-based criterion.The prominent advantage of the proposed approach is that the unambiguous slant-range velocity can be very large.Besides,the first stage is carried out at the determinate range-Doppler test cell by azimuth searching for fitting best to the moving target signal,therefore,the location performance would not be sacrificed in order to suppress clutter and/or interference.The effectiveness and efficiency of the proposed method are validated with a set of airborne experimental data.

Ground moving target detection and location based on SAR images for distributed spaceborne SAR

This paper investigates data processing approaches to detect and locate ground moving targets using distributed spaceborne SAR systems with long cross-track baselines. In particular, it investigates the performance of ground moving target detection for two typical satellite formations： Cartwheel and Pendulum. An approach based on SAR images and a space-time adaptive processing （STAP） algorithm is proposed in order to overcome the effects of the ground terrain on the clutter suppression. The key idea of the approach is firstly to reduce the clutter degrees of freedom greatly by using conventional SAR imaging processing. Then the ground terrain clutter within each SAR pixel can be effectively cancelled by using the very limited spatial degrees of freedom. Finally, constant-false-alarm-rate （CFAR） techniques can be used to detect the remaining target SAR pixels after clutter cancellation. An approach to relocate the detected targets is also proposed, which is based on the estimation of the Doppler spectrum shifts of ground moving targets relative to the clutter Doppler spectrum. The proposed approaches in this paper have the advantages of simplicity and high efficiency.

Sum-difference Reduced-dimensional Processing in SAR Image Domain and Statistical Analysis for Ground Moving Target Indication

In this article, a new reduced-dimensional adaptive processing algorithm based on joint pixels sum-difference data for clutter rejection is proposed. The sum-difference data are obtained by orthogonal projection of the joint pixels data of different synthetic aperture radar （SAR） images generated by a multi-satellite radar system. In the sense of statistical expectation, the sum-difference data contain the common and different information of the SAR images. Therefore, the objective of clutter cancellation can be achieved by adaptive processing. Moreover, based on the residual image after clutter rejection, statistical analysis of constant false-alarm rate （CFAR） detection of moving targets is also presented. Simulation results demonstrate the effectiveness and robustness of the proposed algorithm even with heterogeneous clutter and image co-registration error.

Robust PCA for Ground Moving Target Indication in Wide-Area Surveillance Radar System

Robust PCA has found important applications in many areas,such as video surveillance,face recognition,latent semantic indexing and so on.In this paper,we study its application in ground moving target indication(GMTI)in wide-area surveillance radar system.MTI is the key task in wide-area surveillance radar system.Due to its great importance in future reconnaissance systems,it attracts great interest from scientists.In(Yan et al.in IEEE Geosci.Remote Sens.Lett.,10:617–621,2013),the authors first introduced robust PCA to model the GMTI problem,and demonstrate promising simulation results to verify the advantages over other models.However,the robust PCA model can not fully describe the problem.As pointed out in(Yan et al.in IEEE Geosci.Remote Sens.Lett.,10:617–621,2013),due to the special structure of the sparse matrix(which includes the moving target information),there will be difficulties for the exact extraction of moving targets.This motivates our work in this paper where we will detail the GMTI problem,explore the mathematical properties and discuss how to set up better models to solve the problem.We propose two models,the structured RPCA model and the row-modulus RPCA model,both of which will better fit the problem and take more use of the special structure of the sparse matrix.Simulation results confirm the improvement of the proposed models over the one in(Yan et al.in IEEE Geosci.Remote Sens.Lett.,10:617–621,2013).

FrFT-CSWSF: Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.

Improved STAP algorithm based on APES

Space-time adaptive processing（STAP） has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving target indication（GMTI） radar.This paper applies an amplitude and phase estimation（APES） approach to two aspects of the STAP algorithm.Firstly,APES is applied to accurately describe the clutter characteristic in angle-Doppler domain.Then,APES is incorporated into the standard STAP algorithm to improve its performance without increasing transmitting/receiving channel and pulse number.The experimental examples show that the detection performance can be improved by using the APES technique,as well as the high computational complexity can be avoided.

AN IMPROVED SAR-GMTI METHOD BASED ON EIGEN-DECOMPOSITION OF THE SAMPLE COVARIANCE MATRIX

An improved two-channel Synthetic Aperture Radar Ground Moving Target Indication (SAR-GMTI) method based on eigen-decomposition of the covariance matrix is investigated. Based on the joint Probability Density Function (PDF) of the Along-Track Interferometric (ATI) phase and the similarity between the two SAR complex images, a novel ellipse detector is presented and is applied to the indication of ground moving targets. We derive its statistics and analyze the performance of detection process in detail. Compared with the approach using the ATI phase, the ellipse detector has a better performance of detection in homogenous clutter. Numerical experiments on simulated data are presented to validate the improved performance of the ellipse detector with respect to the ATI phase approach. Finally, the detection capability of the proposed method is demonstrated by measured SAR data.

SAR-GMTI investigation in hybrid along-and cross-track baseline InSAR

A joint-pixel clutter suppression method based on slope compensation is proposed in this paper, In order to eliminate the effect of the terrain interferometric phase caused by the cross-track baseline in hybrid baseline InSAR, the local independent identical distribution of the clutter is satisfied by using the slope compensation technique, and thus the clutter can be suppressed successfully by using the orthogonality of the clutter subspace and the noise subspace. This approach utilizes the information contained in the current pixel as well as in its neighbors, showing robustness to the image coregistration errors. Both the simulated data and the real airborne data are used in proving the validity of the presented approach.