哈尔滨工程大学学报2016，Vol.37Issue(4)：603-607,5.DOI:10.11990/jheu.201412014
采用加权 L1范数稀疏模型构造 DOA 估计的方法
DOA estimation using weighted L1 norm sparse model
摘要
Abstract
For a passive radar system based on a GPS illuminator as the detection signal, estimating direction of arri-val (DOA) of multiple targets in an echo channel with strong interference and low signal-to-noise (SNR) ratio is dif-ficult.Based on the characteristics of GPS-based passive radar system, a DOA estimation method using an improved weighted L1 norm constraint model is proposed.After using the extensive cancellation algorithm ( ECA) to estimate time delay and Doppler frequency shift for removing direct-and multi-path interference, a sparse model for DOA esti-mation is constructed with the L1-norm as a constraint without parameter estimation; DOA estimation is accurately conducted with reduced computational complexity.Simulation results show that the proposed method can perform well with lower computational complexity, and the execution time reduces by 1.18 s compared to the MUSIC-like method with the same configuration.The mean square error is 0.5°~3.7°lower than that of the MUSIC-like and Candes meth-ods, and resolution probability with low SNR is 0.4~0.6 higher than MUSIC-like and Candes method.关键词
GPS辐射源/无源雷达/波达方向/L1范数/批处理抵消算法/稀疏模型/均方误差/分辨概率Key words
GPS illuminator/passive radar/direction of arrival/L1-norm/extensive cancelation algorithm/sparse model/mean square error/resolution probability分类
信息技术与安全科学引用本文复制引用
刘楠,宋文龙,董光辉,冷欣..采用加权 L1范数稀疏模型构造 DOA 估计的方法[J].哈尔滨工程大学学报,2016,37(4):603-607,5.基金项目
国家自然科学基金项目（31270757）；中央高校基本科研业务费专项资金项目（2572014EB03，DL13BB16）；高等学校博士学科点专项科研基金项目（20130062120005）． （）
