层析合成孔径雷达成像航迹分布优化方法

层析合成孔径雷达成像(tomography synthetic aperture radar, TomoSAR)将合成孔径原理用于高程向,通过不同入射角的多幅二维合成孔径雷达图像对高程向反射功率进行重建,从而实现三维成像。TomoSAR中,航迹分布是影响高程向重建的重要因素。针对高程向分布稀疏的情形,压缩感知方法被用于TomoSAR。基于压缩感知的TomoSAR中高程向重建质量取决于观测矩阵的性质,而航迹分布与观测矩阵的重构性能紧密相关。利用一种基于相关系数的观测矩阵优化准则,对航迹分布进行参数优化,从而在航迹数目一定的情况下,实现高程向的优化重建。仿真和实验结果验证了该方法的有效性。

TracK distribution optimization for tomographic synthetic aperture radar imaging

Tomography synthetic aperture radar (TomoSAR) extends the synthetic aperture principle into elevation. It uses measured repeat pass synthetic aperture radar data to reconstruct the backscattered power along elevation, and achieves a three dimensional (3-D) image. In TomoSAR, track distribution affects the quality of elevation reconstruction. Compressive sensing (CS) is used to the elevation reconstruction for the sparse elevation distribution. The imaging quality of TomoSAR based on CS depends on the recovery property of the measurement matrix, which is affected by the track distribution.An optimal criterion based on coherent coefficient is used to optimize the distribution of flight tracks, and achieve the optimal reconstruction of elevation when the amount of tracks is fixed. Simulated and experimental results validate the effectiveness of the optimized method.