Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment

This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches.

Robust Clutter Suppression and Moving Target Imaging Approach for Multichannel in Azimuth High-Resolution and Wide-Swath Synthetic Aperture Radar

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.

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

This paper investigates a new multifrequency compressed sensing (CS) model for 2-D near-field microwave and millimeter-wave synthetic aperture radar (SAR) imaging system, which usually collects multifrequency sparse data. Spatial data of each frequency are represented as a hierarchical tree structure under a wavelet basis and spatial data of different frequencies are modeled as a joint structure, because they are highly correlated. Based on the developed multifrequency CS model, a new CS approach is proposed by exploiting both the intrafrequency and interfrequency correlations, and enriches the existing CS approaches for 2-D near-field microwave and millimeter-wave SAR image reconstruction from undersampled measurements. Combining a splitting Bregman update with a variation of the parallel Fast Iterative Shrinkage-Thresholding Algorithm-like proximal algorithm, the proposed CS approach minimizes a linear combination of five terms: a least squares data fitting, a $\textrm {multi-}\ell _{1}$ norm, a multitotal variation norm, a joint-sparsity $\ell _{21}$ norm, and a tree-sparsity overlapping $\ell _{21}$ norm. Simulation and experimental results demonstrate the superior performance of the proposed approach in terms of both efficiency and convergence speed.

Multifrequency Compressed Sensing for 2-D Near-Field Synthetic Aperture Radar Image Reconstruction

In this study, a novel algorithm for detecting the ground-moving targets and estimating their motion parameters is proposed Based on the fact that clutter has a certain phase pattern, clutter cancellation is accomplished using a phase modification and finite impulse response filtering Then a type of coherent Hough transform is utilised to estimate the moving target velocity By employing the coherent Hough transform, the proposed algorithm leads to the significant signal-to-noise ratio (SNR) and signal-to-clutter ratio improvement in comparison with similar previous Hough- or Radon-based ground-moving target indication and velocity estimation methods In fact, uncorrelated noise samples have random phases that cancel each other, therefore, a noticeable SNR improvement would be achieved Moving target detection is done by conventional constant false alarm rate (CFAR) techniques over different range gates

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rsn.2016.0262

Coherent method for ground-moving target indication and velocity estimation using Hough transform

Wideswath synthetic aperture radar/ground moving targets indication (SAR/GMTI) system increases severely data transmission and storage load. To mitigate this problem, a wideswath GMTI method based on compressed sensing (CS) is proposed. In this method, CS is utilised to process each SAR data sampled sparsely in the azimuth direction for multiple aperture systems after conventional range compression. Then the wavelet transform matrix is used to construct the sparse matrix. Each SAR image is unambiguously achieved by solving l 1 norm optimisation problem in the azimuth. The clutter rejection is performed for all spatial SAR images and then moving targets can be well detected. In this way, the data rate together with storage load is reduced, and then the wideswath GMTI can be efficiently realised. Results of real measured and simulated SAR data processing demonstrate the effectiveness of the CS-based wideswath GMTI.

Wideswath synthetic aperture radar ground moving targets indication with low data rate based on compressed sensing

A novel technique for mitigating the multipath-induced code delay estimation error in Global Positioning System (GPS) is proposed. In contrast to conventional methods that aim to eliminate multipath signals, the proposed method exploits them to enhance the direct signal without affecting the accuracy of GPS code delay estimates. To achieve this, coherent accumulation of the received GPS signals is first done by transforming the received data into frequency domain and the parameters of multipath signals are then estimated by sparse reconstruction algorithm. Subsequently, a modified local reference signal is employed in delay lock loop (DLL) of the GPS receiver, which mitigates the pseudo-range estimation error and increases the correlation value of direct GPS signal. Simulation results demonstrate the performance and robustness of the proposed method.

A multipath mitigation discriminator for GPS receiver

Ground moving targets indication (GMTI) system based on dual-channel Synthetic Aperture Radar (SAR) increases data transmission and storage load. To alleviate such payloads, we propose a GMTI method using weighted l 1 optimization with reduced amount of echo samples. In this method, compressive sensing (CS) is utilized to process jointly the dual channel SAR data sampled sparsely in the azimuth direction. A transform matrix is firstly constructed to separate the energy support areas of moving targets from the energy support areas of all scattering centers. Then, clutter suppression and moving target imaging are achieved by solving a weighted l 1 norm optimization. The proposed method works well even if clutter scattering centers have a low sparse level. Simulation results demonstrate the effectiveness of the method.

Dual channel SAR-based GMTI using weighted l 1 optimization

The conventional ScanSAR imaging method acquires wide swath coverage at a cost of severe azimuth resolution loss. To mitigate this problem, a Scan-SAR imaging method using compressive sensing theory (CS) is proposed in this paper. In the proposed method, the matched filter is firstly used to perform pulse compression in the range direction. Then, CS is utilized to process jointly all bursts of each subswath by solving an l1 minimization optimization. The proposed method can achieve the azimuth SAR imaging with a high azimuth resolution. Furthermore, it overcomes the scalloping problem of ScanSAR. Simulated and real data experiments demonstrate the effectiveness of the proposed method. (5 pages)

http://ieeexplore.ieee.org/iel7/6482821/6494711/06494874.pdf

Weiwei Wang

Papers

Wideswath synthetic aperture radar ground moving targets indication with low data rate based on compressed sensing

A multipath mitigation discriminator for GPS receiver

Dual channel SAR-based GMTI using weighted l 1 optimization

A ScanSAR imaging method using compressive sensing