稀疏步进频合成孔径雷达成像算法

提出了一种适用于稀疏步进频信号的成像算法,以较少的时间和频谱资源完成了雷达目标成像。该算法将稀疏步进频回波数据等效为均匀步进频回波数据的观测值,利用压缩感知重构算法实现目标区域的距离向重构,然后经过距离徙动校正与方位向脉压完成对目标场景成像。仿真结果表明:该算法在发射频点高度稀疏条件下仍能实现高分辨成像。采用地基雷达实测数据验证了算法的有效性。

An Imaging Algorithm of SAR Using Sparse Stepped Frequency Waveform

Ultra-wideband frequency-stepped signal is an effective radar signal, but its anti-jiamming ability is not enough, and its pulse-width time is too long. To solve these problems, an imaging algorithm based on sparse frequency-stepped signal is proposed, the use of which can complete the target imaging with less resource of time and spectrum. In the proposed algorithm, the echo data of sparse frequency-stepped signals are equivalent to the observed values of the echo data of the traditional frequency-stepped signals. Therefore, the reconstruction of the high-resolution range profile can be realized based on the compressive sensing (CS) theory. Then, the target scene imaging can be completed by range cell migration correction and azimuth pulse compression. The simulation results demonstrate that the use of the algorithm can achieve a high-resolution imaging while the transmitted frequency-stepped signal is sparse in frequency domain. Finally, the ground-based radar experiment data are adopted to verify the effectiveness of the proposed algorithm.