基于改进平滑l0范数的均匀圆阵DOA估计方法

doi:10.16182/j.issn1004731x.joss.201710015

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (10): 2336-2344.doi: 10.16182/j.issn1004731x.joss.201710015

基于改进平滑l₀范数的均匀圆阵DOA估计方法

王彪, 陈峰, 陆丽

江苏科技大学电子信息学院,江苏镇江 212003

收稿日期:2015-10-10 发布日期:2020-06-04
作者简介:王彪(1980-),男,甘肃张掖,博士生,副教授,硕导,研究方向为水声阵列信号处理及水声通信技术。
基金资助:
国家自然科学基金(11574120,61401180),江苏省高校自然科学基金(12KJB510003,13KJB5100 07), 江苏省高校优势学科建设工程, 江苏省研究生科研与实践创新计划项目（SJCX17_0604）,江苏省“青蓝工程”资助的课题

DOA Estimation Method of Uniform Circular Array Based on Improved Smoothed l₀ Norm

Wang Biao, Chen Feng, Lu Li

School of Electronic and Information, Jiangsu University of Science and Technology, Zhenjiang 212003, China

Received:2015-10-10 Published:2020-06-04

摘要/Abstract

摘要： 针对传统窄带信号的DOA估计方法中存在分辨率低、不适用于低快拍以及阵元数较少的应用场合等问题,在分析了均匀圆阵模型以及目标空域稀疏特性后,结合改进平滑l₀范数重构算法,提出了基于改进平滑l₀范数的均匀圆阵DOA方法。该方法在利用稀疏矩阵处理阵列流形的基础上,通过选取组合函数作为近似估计l₀范数的函数进行信号重构,提高收敛速度,并将其扩展到均匀圆阵DOA估计方法中,避免了特征分解和谱峰搜索过程,在保证估计分辨率的前提下,有效降低了计算量,减小天线的阵元数目。通过实验仿真,从而验证了该方法的可行性与有效性。

关键词: 窄带信号, 均匀圆阵, DOA估计, 空域稀疏性, 改进平滑l₀范数

Abstract: To solve the problems of the narrow-band signal DOA method, such as low resolution and unsuitable for applications with small number of snapshot and array elements, etc, DOA of uniform circular array based on improved smoothed l₀ norm was proposed after analysis of the characteristics of UCA model and signal airspace sparse, combining with improved the smooth l₀ norm algorithm. For reconstructing the signal, the method used the combined continuous function as the approximation to l₀ norm by sparse matrix processing array manifold, which improved the convergence speed. It was also extended to the UCA DOA estimation, which avoided feature decomposition and spectral peak searching process. On the premise of guarantee the estimation precision, the calculation and the number of the array were effectively reduced. The feasibility and effectiveness of the method were verified by the experimental simulation.

Key words: narrow-band signal, uniform circular array, DOA, space sparsity, improved smoothed l₀ norm

中图分类号:

TP391.9

王彪, 陈峰, 陆丽. 基于改进平滑l₀范数的均匀圆阵DOA估计方法[J]. 系统仿真学报, 2017, 29(10): 2336-2344.

Wang Biao, Chen Feng, Lu Li. DOA Estimation Method of Uniform Circular Array Based on Improved Smoothed l₀ Norm[J]. Journal of System Simulation, 2017, 29(10): 2336-2344.

参考文献

[1] 吴畏, 闫鲁生, 黄本雄, 等. 基于工程应用的圆形阵列方向特性研究[J]. 系统仿真学报, 2011, 23(3): 536-541.
(Wu Wei, Yan Lu-Sheng, Huang Ben-xiong, et al.Study of Direction Characteristic of Circular Array Based on Application of Project[J]. Journal of System Simulation, 2011, 23(3): 536-541.)
[2] Capon J.High-resolution frequency-wave number spectrum analysis[J]. Proceedings of the IEEE (S0018-9219), 1969, 57(8): 1408-1418.
[3] Schmidt R.Multiple emitter location and signal parameter estimation[J]. Antennas and Propagation, IEEE Transactions on(S0018-926X), 1986, 34(3): 276-280.
[4] Baraniuk R.Compressive sensing[J]. IEEE Signal Processing Magazine(S1053-5888), 2007, 24(4): 118-121.
[5] 赵瑞珍, 林婉娟, 李浩, 等. 基于光滑10范数和修正牛顿法的压缩感知重建算法[J]. 计算机辅助设计与图形学学报, 2012,24(04):478-484.
(Zhao Rui-Zhen, Lin Wan-Juan, Li Hao, et al.Reconstruction Algorithm for Compressive sensing Based on Smoothed l0 Norm and Revised Newton Method[J].Journal of Computer-Aided Design and Computer Graphics, 2012,24(04):478-484.)
[6] 王彪, 李超, 李宇, 等. 一种快速水声目标波达方向估计方法[J]. 声学学报, 2014,39(05):544-548.
(Wang Biao,Li Chao,Li Yu,et al.A fast direction of arrival estimation method for underwater acoustic target[J]. ACTA ACUSTICA, 2014,39(05):544-548.)
[7] Bilik I.Spatial compressive sensing for direction of arrival estimation of multiple sources using dynamic sensor arrays[J]. IEEE Transactions on Aerospace and Electronic Systems(S0018-9251), 2011, 47(3): 1754-1769.
[8] 胡南. 基于稀疏重构的阵列信号波达方向估计算法研究 [D]. 合肥: 中国科学技术大学, 2013.
(Hu Nan.Direction of Arrival Estimation Algorithm for Array Signals based on Sparse Signal Reconstruction[D] . Hefei, China: University of Science and Technology of china, 2013.)
[9] Cai T, Xu G, Zhang. On recovery of sparse signals via l₁ minimization[J]. IEEE Trans. Inf. Theory (S0018-9448), 2009, 55(7): 3388-3397.
[10] Hosen Mohimani G, Massoud Babaie-Zadeh, Christian Jutten.A fast approach for over-complete sparse decomposition based on smoothed l0 norm[J]. IEEE Transactions on Signal Processing (S1053-587X), 2009, 57(1): 289-301.
[11] Ghalehjegh S H, Babaie-Zadeh M, Jutten C.Fast block-sparse decomposition based on sl0[C]// 9^th International Conference on Latent Variable Analysis and Signal Separation. Springer Berlin Heidelberg, 2010, 6365: 426-433.
[12] 林婉娟, 赵瑞珍, 李浩. 用于压缩感知信号重建的NSL0算法[J]. 新型工业化, 2011, 1(7): 78-84.
(Lin Wan-Juan, Zhao Rui-Zhen, Li Hao.The NSL0 Algorithm for Compressive Sensing Signal Reconstruction[J]. The Journal of New Industrialization,2011, 1(7): 78-84.)
[13] 王彪, 李超, 戴跃伟. 基于空域压缩采样的水声目标 DOA 估计方法[J]. 兵工学报,2013,34(11):1479-1483.
(Wang Biao,Li Chao,Dai Yue-Wei.DOA Estimation Method Based on Spatial Compressive Sampling for Underwater Acoustic Target[J]. ACTA ARMAMENTARII, 2013, 34(11): 1479-1483.)

基于改进平滑l₀范数的均匀圆阵DOA估计方法

DOA Estimation Method of Uniform Circular Array Based on Improved Smoothed l₀ Norm

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