期刊论文

中文

计算机仿真

1006-9348

2015

32

4

9-12,413

本校为第一机构

研究基于改进的无源雷达WSN信号采集模型仿真。无源雷达WSN信号采集过程中,无源雷达信号的稀疏度很高,并且信号未知度较高。传统的信号采集方法应用到该领域时,需要进行较大规模的重构,以保证信号密度,才能完成采集,但是由于无源雷达的WSN信号的未知度过高,重构过程复杂,信号采集过程耗时。提出了一种有效的基于改进无源雷达WSN信号采集方案,首先通过稀疏压缩感知获得节点的数据测量数值,并通过随机投影进行采集测量数据,其次在节点中引入的高斯矩阵对所获的测量值进行编码,通过拉格朗日松弛函数将这些编码进行处理,得到近似最优解,从而获得了一种有效的无源雷达传感信号采集方案。仿真结果表明...

During WSN signal acquisition of passive radar, the signal represents a highly sparse and unknown degree. When the traditional signal acquisition method is applied to the field, large- scale reconstruction is needed to ensure that the signal density and then complete the acquisition. But WSN signal of passive radar possesses a high degree of uncertainty, the reconstruction process is complex and signal acquisition process is time - consuming. This paper proposes an improved WSN signal acquisition program for passive radar. The program first gets measured values of node data by sparse compresse...