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作 者:王伟东 张群飞[1] 史文涛[1] 谭伟杰[1] 王绪虎 WANG Weidong;ZHANG Qunfei;SHI Wentao;TAN Weijie;WANG Xuhu(School of Marine Science and Technology,Northwestern Polytechnic University,Xi’an 710072,China;School of Information and Control Engineering,Qingdao University of Technology,Qingdao 266520,China)
机构地区:[1]西北工业大学航海学院,西安710072 [2]青岛理工大学信息与控制工程学院,青岛266520
出 处:《振动与冲击》2020年第15期48-57,共10页Journal of Vibration and Shock
基 金:国家重点研发计划(2016YFC1400203);国家自然科学基金(61531015;61501374)。
摘 要:针对现有稀疏信号功率迭代算法对方位相近目标分辨概率与估计精度较低问题,提出了一种稀疏信号功率迭代补偿的矢量传感器阵列波达方向(Direction of Arrival, DOA)估计方法。基于稀疏信号补偿原理和加权协方差矩阵拟合准则,构建了关于稀疏信号功率与补偿权重的目标函数。推导了稀疏信号功率迭代更新表达式的闭式解。通过对稀疏信号功率进行谱峰搜索获得DOA估计值。理论分析表明,所提算法通过对离散网格点上的信号功率进行补偿提高了方位相近目标的分辨率概率与估计精度。仿真结果表明,相较于经典子空间算法与现有稀疏功率迭代算法,所提算法对方位相近目标具有较高的分辨概率与估计精度。Aiming at the problem of the existing sparse signal power iterative algorithm having lower resolution probability and estimation accuracy for targets with similar azimuth, a sparse signal power iteration compensation method was proposed to estimate direction of arrival(DOA) via vector sensor arrays. Firstly, based on the principle of sparse signal compensation and the fitting criterion for weighted covariance matrix, the objective function regarding sparse signal power and compensation weight was constructed. Secondly, the closed-form solution to sparse signal power iteration renewal expression was derived. Finally, DOA estimation was obtained through searching spectral peaks of sparse signal power. The theoretical analysis showed that the proposed algorithm can improve the resolution probability and estimation accuracy for targets with similar azimuth by compensating signal power values at discrete grid points. Simulation results showed that compared with the classical subspace algorithm and the existing sparse power iteration algorithm, the proposed algorithm has higher resolution probability and estimation accuracy for targets with similar azimuth.
关 键 词:矢量传感器阵列 加权协方差矩阵 稀疏信号功率补偿 波达方向估计
分 类 号:TG156[金属学及工艺—热处理]
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