利用二维结构稀疏信息的调频步进ISAR高分辨成像新方法

针对已有利用压缩感知理论进行逆合成孔径（Inverse Synthetic Aperture Radar,ISAR）成像方法在低信噪比、欠采样率条件下性能下降严重等问题,依托调频步进波形独有特征并充分利用目标分布的二维结构稀疏信息,提出一种"先方位聚焦后距离分辨"的调频步进ISAR高分辨成像新方法.首先,对回波进行子脉冲脉压,在分析调频步进ISAR回波方位向特有的结构稀疏特征基础上,构建方位向的分布式压缩感知稀疏重构模型;其次,采用分布式压缩感知算法对该模型重构,从而获得低信噪比条件下的方位高分辨成像;最后,利用距离维的回波特征构建任意稀疏重构模型,实现距离向快速成像.由于该方法先进行方位聚焦,再进行距离分辨,并充分利用了目标的结构稀疏性,因此不仅具有抗噪性能强、重构精度高以及采样率低等特点,且避免了越距离单元走动对方位聚焦的影响.仿真与实测数据实验验证了本文方法的有效性.

A New High Resolution Chirp Frequency Stepped ISAR Imaging Algorithm by Using Two-Dimensional Sparse Structure Information

In order to improve the performance of the ISAR imaging method based on compressed sensing under sub-sampling and low SNR,a new high resolution ISAR imaging method for chirp frequency stepped signal is proposed,based on the unique characteristics of the stepped frequency waveform,and the two-dimensional sparse structure information of the target.The proposed method is deal with the cross range focusing first and then the range resolution.Firstly,the pulse compression is performed on the sub-pulse echo,and then based on the analysis of the sparse structure of the stepped frequency ISAR echo in cross range dimension,a distributed compressed sensing model is constructed;Secondly,the DCS-SOMP algorithm is used to reconstruct the model,then the high cross range resolution imaging in low SNR is obtained;Finally,an arbitrary sparse representation model is constructed by using the echo characteristics in range dimension.Because the proposed method,which is cross range focusing first and then the range resolution,makes full use of the target structure,it not only avoids the migration through range resolution cell effect on the cross range resolution,but also has strong anti-noise performance,high reconstruction accuracy and low sampling rate.The validity of the proposed method is verified by simulation and experimental data.