摘要
针对现有融合识别算法难以兼顾信息完备性和节点通信数据量的问题,提出一种基于信号稀疏表示的雷达辐射源信号级融合识别算法.该方法将接收信号投影到稀疏域并进行压缩,从而在稀疏域完成融合,最后利用融合后的稀疏系数进行识别.该方法既降低了通信数据量,又较好地保证了信息的完整性.仿真实验表明,相对于单一传感器和决策级融合,所提出的方法可有效提高信号识别性能.
To solve the contradiction between the information completeness and data volume existing in the radar signal fusion, a signal-level fusion algorithm for radar emitter identification based on sparse representation is presented. In the algorithm, intercepted signals are projected to sparse domains and compressed for communication. Then the sparse coefficients are fused for recognition. The data of communication is decreased in the algorithm, and the available information of intercepted signal is also reserved. The simulations show that the recognition accuracy is improved compared with the single signal receiver and the decision-level fusion algorithms.
出处
《控制与决策》
EI
CSCD
北大核心
2014年第10期1798-1802,共5页
Control and Decision
基金
国家自然科学基金项目(60901069)
国家863计划项目(2011AAXXXX061)
关键词
雷达辐射源
辐射源识别
数据融合
稀疏表示
信号级融合
radar emitter
emitter identification
data fusion
sparse representation
signal-level fusion
