提出一种基于压缩感知(CS)技术在机会雷达系统中进行恒虚警率(CFAR)目标检测的算法, 根据目标回波在距离单元上的稀疏性, 采用压缩感知技术对目标回波进行压缩采样；设计了一种新的建立在压缩域上的CA-CFAR检测器, 它能在不恢复原始信号的条件下, 快速完成目标回波的检测；进行了检测门限理论分析, 设计出一种适用于压缩域检测的门限选定方法；给出系统检测结果与接收机的性能曲线。仿真结果表明, 本算法可以实现低信噪比下雷达信号的直接检测, 无需信号重构, 节省了运算量。

An algorithm based on Compressive Sensing(CS) technology is proposed, which is applied in the opportunistic radar system, conducting Constant False Alarm Rate(CFAR) target detection. Because of the sparseness of the target echo on the distance unit, a new CA-CFAR detector based on the compressed domain is designed by using the compression sensing sample. In this way, the target echo can be found without restoring the original signal. The algorithm can achieve target echo detection rapidly. And the theoretical analysis of the detection threshold of the CA-CFAR detector on the compressed domain is further studied. The performance of the system and the characteristic of the receiver are given. The simulation results show that the algorithm can directly detect the low SNR signal without signal reconstruction and cut the computation amount.