Application of Road Information in Ground Moving Target Tracking

A new algorithm is developed to achieve accurate state estimation in ground moving target tracking by means of using road information. It is an adaptive variable structure interacting multiple model estimator with dynamic models modification （DMM VS-IMM for short）. Firstly, road information is employed to modify the target dynamic models used by filter, including modification of state transition matrix and process noise. Secondly, road information is applied to update the model set of a VS-IMM estimator. Predicted state estimation and road information are used to locate the target in the road network on which the model set is updated and finally IMM filtering is implemented. As compared with traditional methods, the accuracy of state estimation is improved for target moving not only on a single road, but also through an intersection. Monte Carlo simulation demonstrates the efficiency and robustness of the proposed algorithm with moderate computational loads.

RADAR HRR PROFILING FOR GROUND MOVING TARGET USING PHASE-CODED AND HOPPED-FREQUENCY WAVEFORMS

To obtain the radar High Range Resolution (HRR) profile of the slowly moving ground target in strong clutter background, the Phase-Coded Hopped-Frequency (PCHF) waveform is proposed. By multiple-bursts coherent processing, the HRR profile synthesis, target velocity compensation and clutter compression can be accomplished simultaneously. The new waveform is shown to have good ability to suppress ground clutter and good Electronic Counter-CounterMeasures (ECCM) ability as well. The clutter compression performance of the proposed method is verified by the numerical results.

Ground Moving Target Tracking with VS-IMM Using Mean Shift Unscented Particle Filter

In order to track ground moving target, a variable structure interacting multiple model （VS-IMM） using mean shift unscented particle filter （MS-UPF） is proposed in this paper. In model-conditioned filtering, sample particles obtained from the unscented particle filter are moved towards the maximal posterior density estimation of the target state through mean shift. On the basis of stop model in VS-IMM, hide model is proposed. Once the target is obscured by terrain, the prediction at prior time is used instead of the measurement at posterior time; in addition, the road model set used is not changed. A ground moving target indication （GMTI） radar is employed in three common simulation scenarios of ground target： entering or leaving a road, crossing a junction and no measurement. Two evaluation indexes, root mean square error （RMSE） and average normalized estimation error squared （ANEES）, are used. The results indicate that when the road on which the target moving changes, the tracking accuracy is effectively improved in the proposed algorithm. Moreover, track interruption could be avoided if the target is moving too slowly or masked by terrain.

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.

Ground moving target signal model and power calculation in forward scattering micro radar

Forward scattering micro radar is used for situation awareness; its operational range is relatively short because of the battery power and local horizon, the free space propagation model is not appropriate. The ground moving targets, such as humans, cars and tanks, have only comparable size with the transmitted signal wavelength; the point target model and the linear change of observation angle are not applicable. In this paper, the signal model of ground moving target is developed based on the case of forward scattering micro radar, considering the two-ray propagation model and area target model, and nonlinear change of observation angle as well as high order phase error. Furthermore, the analytical form of the received power from moving target has been obtained. Using the simulated forward scattering radar cross section, the received power of theoretical calculation is near to that of measured data. In addition, the simulated signal model of ground moving target is perfectly matched with the experimented data. All these results show the correctness of analytical calculation completely.

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).

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.

Highly robust ground moving target detection and relocation method for distributed satellites

The performance of ground moving target detection for distributed satellites will be affected signifi-cantly when there is an image registration error,clutter decorrelation and array error.In this paper,a new approach to moving target detection and relocation is proposed based on multi-channel and multi-pixel adap-tive signal processing in an image domain.First,multi-channel and multi-pixel joint data are equated to a simple array model.Given that there is an image registration error,the real steering vector of the moving target can be estimated through a space projection approach.The optimal beam forming approach is used to cancel clutter,and at the same time the cross-track velocity of the mov-ing target can be determined by searching for the peak value of the cost function.The moving target can then be relocated on the SAR image.The simulation results indicate that this method has a good robustness to image registration error,clutter decorrelation and array error.The detection performance and the estimation accuracy are significantly improved.

High-speed ground moving target detection research using triangular modulation FMCW

The frequency modulated continuous wave(FMCW)radar has the characteristics of low probability of interception,good hidden property and the ability to counter anti-radiation missiles.This paper proposes a new method for high-speed ground moving target detection(GMTD)using triangular modulation FMCW.According to the characteristic of the opposite range shift induced by the upslope and downslope modulation FMCW,the upslope and downslope are imaged,respectively.After compensation of continuous motion of the platform and time difference between upslope and downslope signals for imaging,the moving target can be detected through displaced phase center antenna(DPCA)technology.When the moving target is detected,the moving target image is extracted,and correlation processing is used to obtain the range shift,which can be used to estimate the target radial velocity,and further to find the real position of the target.The effectiveness of this method is verified by the result of computer simulation.

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.

REAL EXTENDED SCENE AND MOVING TARGET MULTI-CHANNEL SAR RAW SIGNAL SIMULATION

A real extended scene and moving targets multi-channel Synthetic Aperture Radar(SAR) raw signal simulator accounting for Inertial Navigation System(INS) errors and antenna patterns is presented in this paper. INS errors are obtained by solving INS error differential equations with Runge-Kutta method. A high resolution SAR image is used to estimate the complex reflectance of real extended scene. Extended scene and moving target are simulated separately and then are superposed in time domain. The simulated multi-channel SAR data can be used for development of multi-channel SAR Ground Moving Target Indication(SAR-GMTI) and also can be used for development of SAR motion compensation.

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.

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.

BACKSIDE EFFECT OF BISTATIC AIRBORNE CLUTTER CHARACTERISTICS AND ITS APPLICATIONS IN GMTI

An interesting clutter characteristic of bistatic radars is presented, which is named as backside effect. In such an effect, the range-dependent ground clutter spectrum can be easily aligned, and Space-Time Adaptive Processing (STAP) is to be more applicable and effective for the Ground Moving Target Indication (GMTI) in bistatic systems. The backside effect is proved by the numerical calculation method and explained in point of the geometry. At last a new spectrum aligning method is induced, i.e., ADC and Rotation (ADCR), which can gain a further performance improvement on GMTI.

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.