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针对复杂电磁环境下,大量的信号在时间、空间、频谱发生随机交叠时,现有分选方法很难进行分辨的问题,提出了一种基于压缩感知理论的雷达信号分选算法.该算法将信号的样本空间作为稀疏字典,将待分选的雷达信号进行稀疏表示,以少量的观测数据就能获取信号的全部信息,从而对雷达信号进行有效的分选.仿真结果表明,该算法能对大量时频交叠信号进行快速分选,且在低信噪比下也能取得较理想的效果.
In complex electromagnetic environment, a large number of signals in the time, space, frequency spectrum random overlap, the existing sorting method is difficult to distinguish the problem, this paper proposes a compression sensing theory based radar signal sorting algorithm. Taking the sample space of the signal as a sparse dictionary, the radar signal to be sorted is sparsely expressed, and all the information of the signal can be obtained with a small amount of observation data, so as to effectively sort the radar signal. The simulation results show that the algorithm can A large number of time-frequency overlapping signal for rapid sorting, and can also achieve better results at low SNR.