Compared to traditional bistatic synthetic aperture radar (BiSAR), spaceborne-airborne bistatic linear array SAR (SA-BiLASAR) demonstrates huge advantages for forward-looking and down-looking 3-D observation. But limited by the Rayleigh limitation, classical data processing is hard to produce high resolution image with a short linear array antenna. In this paper, a high resolution imaging method based on compressive sensing theory is proposed for SA-BiLASAR 3-D imaging by exploiting its sparsity. Firstly, the principle and the signal model of the SA-BiLASAR are presented with its prior sparsity, and we pose SA-BiLASAR 3-D imaging procedure as solving sparse solutions to an under-determined linear equation. Secondly, a data-segmented l1-norm minimization is introduced for SA-BiLASAR 3-D imaging, where a low resolution image obtained by back projection algorithm is used to estimate the sparse scattering area. Lastly, the proposed method is validated by numeral simulation data, the results demonstrate that the exploiting of scene sparsity can produce a better quality 3-D image compared with the conventional method.
['Shun-Jun Wei', 'Xiaoling Zhang', 'Jun Shi']
Spaceborne-airborne bistatic linear array SAR high resolution 3-D imaging based on sparsity exploiting