动态压缩感知波达方向跟踪算法

doi:10.13229/j.cnki.jdxbgxb20170585

摘要/Abstract

摘要：

针对现有动态目标波达方向(DOA)跟踪方法在单快拍条件下估计精度较低甚至失效的问题,提出了一种基于动态压缩感知的DOA跟踪算法。首先,通过前一跟踪时刻所得到的先验DOA稀疏信息,获得当前跟踪时刻信号向量中各位置非零元素的分布概率,继而建立起动态DOA的稀疏概率模型。然后,采用加权l₁范数最小化方法重构出当前跟踪时刻的信号向量,从而确定非零元素的位置,获得DOA的实时估计值,最终实现运动目标的动态DOA跟踪。本文算法可以在单快拍条件下实现对动态目标DOA的良好跟踪,并且在相同条件下具有比粒子滤波算法更好的跟踪性能。最后,通过仿真试验对所提算法进行了有效性验证。

关键词: 信息处理技术, 波达方向跟踪, 动态压缩感知, 稀疏概率模型, 加权l₁范数最小化

Abstract:

In order to solve the problem that the performance of Direction of Arrival (DOA) tracking of dynamic target algorithm deteriorates under single snapshot, a DOA tracking method using dynamic compressed sensing is proposed in this article. Firstly, by extracting priori information about sparsity from last signal vector, we estimate the probability of the elements being non-zero and build a sparsity probability model of dynamic DOA in the present signal vector. Secondly, we get the locations of nonzero elements of present signal vector and achieve real-time DOA tracking of dynamic targets by applying this sparsity probability model to the reconstruction of sparse signals and minimizing a weighted norm. This method can obtain real-time DOA tracking of dynamic targets in a single snapshot condition and has better tracking performance than particle filter under the same conditions. Finally, the effectiveness of proposed algorithm is verified by numerical simulation results.

Key words: information processing technology, direction of arrival(DOA) tracking, dynamic compressed sensing, sparsity probability model, weighted l₁ minimization

中图分类号:

TN911

单泽彪,刘小松,史红伟,王春阳,石要武. 动态压缩感知波达方向跟踪算法[J]. 吉林大学学报(工学版), 2018, 48(6): 1938-1944.

SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing[J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.

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