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

Review on interferometric ISAR 3D imaging: Concept, technology and experiment

In this paper, the squint mode multi-channel (MC) synthetic aperture radar (SAR) with hybrid baseline and fluctuant terrain is proposed and studied for high-resolution and wide-swath (HRWS) imaging. During the imaging process, due to the cross-track baseline and fluctuant terrain, the azimuth signal reconstruction is the kernel problem for this imaging mode. To deal with this problem, in this paper a robust azimuth signal reconstruction approach is proposed, where terrain elevation of scene is considered. At first, the pre-processing of the linear range cell migration correction (RCMC) and topography-independent phase compensation is implemented in the azimuth time domain. After that, combining the azimuth echo signal characteristics, the local polynomial Fourier transform (LPFT) is utilized to obtain the coarse-focused SAR image. Then, based on joint pixel pair vector and robust Capon beamforming (RCB), a Doppler ambiguity suppression approach is proposed to reconstruct the Doppler ambiguity-free azimuth signal in LPFT frequency domain, during which the influence of the cross-track baseline component and fluctuant terrain is eliminated using the coarse digital elevation model (DEM) for the imaging scene. At last, the chirp scaling imaging algorithm is utilized to focus the SAR image. The effectiveness of the proposed imaging approach is demonstrated via simulated and real measured squint mode MC-HRWS SAR data.

A Robust Imaging Algorithm for Squint Mode Multi-Channel High-Resolution and Wide-Swath SAR With Hybrid Baseline and Fluctuant Terrain

Clutter suppression and ground moving target imaging approach for hypersonic vehicle borne multichannel radar based on two-step focusing method

SAR raw data signal to noise ratio (SNR) after compression is of great importance since the choice of compression ratio is dependent on it during SAR system design and application analysis. The signal to quantization noise ratio (SQNR) generally used may not precisely indicate the relationship between signal and noise. Considering the thermal noise, a statistical model of quantization interval transfer probability is proposed in this paper. SNR mapping between SAR raw data before analog to digital converter (ADC) and after block adaptive quantization (BAQ) over the whole set of saturation degree is obtained using this model. When the power of echo is small with low SNR, after 1, 2, 3 or 4 bits BAQ compression, SNR has tiny difference among the four compression levels. When the power of the echo is medium with higher SNR, the SNR degradation after BAQ is about 5 dB with each bit decreasing from 4 bits. If voltage of the echo is higher than the clipping point of ADC, SNR after ADC and BAQ degrades stepwise. The higher the saturation degree of SAR raw data, the worse the SNR is. Simulated Gaussian data and real SAR raw data are used to verify the theoretical results, which are useful in the choice of BAQ compression ratio and further application analysis.

https://link.springer.com/content/pdf/10.1007%2Fs11432-010-4082-x.pdf

A study of spaceborne SAR raw data compression error based on a statistical model of quantization interval transfer probability

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.

JianXin Wu

Papers

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