针对雷达目标识别中散射中心特征提取需求,提出一种基于压缩感知理论(CS)的超分辨散射中心估计算法。通过设计一字典,将脉压波形进行稀疏表示,进而将重构问题引入CS 理论框架之下,利用仿真数据验证了散射中心重构算法的可行性。基于实录数据,将80 MHz 宽带信号滤波成20 MHz 窄带信号,利用窄带20 MHz 脉压波形重构高分辨散射中心,进而恢复宽带80 MHz 脉压信号。恢复信号与真实80 MHz 宽带脉压信号的对比分析结果表明,在一定误差范围内,CS算法可实现目标散射中心重构。

Due to the requirement for feature extraction of scattering centers in radar target recognition, a method of super-resolution scattering center parameters estimation based on compressed sensing is proposed. By designing a dictionary, pulse compression signal is sparsely represented in this paper and then the CS framework is used to the reconstruction problem. Based on the simulation method, the correctness of our proposed scheme is verified. Through filtering a signal with 80 MHz bandwidth into a 20 MHz narrow-band signal, the super-resolution scattering centers are reconstructed by the 20 MHz signal and then wideband pulse compressed signal is recovered. Results show that the proposed algorithm is feasible to reconstruct scattering centers with an acceptable error.

TN97