摘要
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.
The traditional radar signal sorting methods are concentrated in feature difference in time,space and frequency domains for signal separation and detection. The random overlapping signals of time,space and spectrum in the complicated electromagnetic environment make the existing methods difficult to distinguish. For these problems,a new radar signal sorting algorithm based on the compressed sensing was proposed. The radar signals for sorting can be represented sparsely in dictionary constituted by signal samples. The algorithm can obtain all the information with a small amount of observational data,the radar signals are sorted effectively. Simulation indicates that the signals can be rapidly sorted using this algorithm and the desired results are obtained in low signal noise ratio.
出处
《北京邮电大学学报》
EI
CAS
CSCD
北大核心
2016年第2期82-87,共6页
Journal of Beijing University of Posts and Telecommunications
基金
中央高校基本科研业务专项资金资助项目(JDZD140503)
关键词
信号分选
压缩感知
样本空间
稀疏字典
稀疏表示
signal sorting
compressed sensing
sample space
sparse dictionary
sparse representation