非平稳噪声下稀疏表示的DOA估计算法

doi:10.13190/j.jbupt.2019-049

北京邮电大学学报 ›› 2020, Vol. 43 ›› Issue (1): 116-121.doi: 10.13190/j.jbupt.2019-049

非平稳噪声下稀疏表示的DOA估计算法

韦娟¹, 曹凯军¹, 宁方立^2,3

1. 西安电子科技大学通信工程学院, 西安 710071;
2. 西北工业大学机电学院, 西安 710072;
3. 东莞市三航军民融合创新研究院, 东莞 523808

收稿日期:2019-04-04 出版日期:2020-02-28 发布日期:2020-03-27
作者简介:韦娟(1973-),女,副教授,E-mail:weijuan@xidian.edu.cn.
基金资助:
国家自然科学基金项目（51675425）；2018年东莞市社会科技发展（重点）项目（20185071021600）；陕西省重点研发计划项目（2018SF-365，2018GY-181）

DOA Estimation Algorithm for Sparse Representation Under Non-Stationary Noise

WEI Juan¹, CAO Kai-jun¹, NING Fang-li^2,3

1. School of Telecommunications Engineering, Xidian University, Xi'an 710071, China;
2. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
3. Dongguan Sanhang Civil-Military Integration Innovation Institute, Dongguan 523808, China

Received:2019-04-04 Online:2020-02-28 Published:2020-03-27
Supported by:

摘要/Abstract

摘要： 为提高非平稳噪声下远场非相干窄带信号波达方向（DOA）的估计精度，提出了一种基于稀疏重构的DOA估计算法.采用类协方差差分算法构造差分矩阵，抑制非平稳噪声的影响；基于类旋转不变子空间参数估计算法基本原理构造稀疏表示模型与权函数；利用加权l₁范数对模型求解，实现DOA估计.仿真结果表明，与传统的协方差差分算法、噪声协方差矩阵估计算法、秩迹最小化算法以及稀疏重构算法相比，所提算法不仅能较好地抑制非平稳噪声的影响，而且在低信噪比、低快拍数情况下具有较强的稳健性和较高的估计精度.

关键词: 非平稳噪声, 波达方向估计, 稀疏重构, 加权l₁范数

Abstract: In order to improve the direction of arrival (DOA) estimation accuracy of the far-field non-coherent narrow-band signal in non-stationary noise environment, an improved DOA estimation algorithm based on sparse reconstruction is proposed. Firstly, the class differential covariance algorithm is used to construct the difference matrix to suppress the influence of non-stationary noise. Then the sparse representation model and the weight function is constructed based on the basic principle of estimation of signal parameters via rotational invariance technique algorithm. Finally, the DOA estimation is realized by solving the model with weighted l₁ norm. Simulation shows that, compared with the traditional covariance difference algorithm, the noise covariance matrix estimation algorithm, the rank trace minimization algorithm, the sparse reconstruction algorithm, the proposed algorithm can not only suppress the influence of non-stationary noise effectively, but also has strong robustness and high estimation accuracy under low signal noise ratio and low snapshot number.

Key words: non-stationary noise, direction of arrival estimation, sparse reconstruction, weighted l₁ norm

中图分类号:

TN911.7

韦娟, 曹凯军, 宁方立. 非平稳噪声下稀疏表示的DOA估计算法[J]. 北京邮电大学学报, 2020, 43(1): 116-121.

WEI Juan, CAO Kai-jun, NING Fang-li. DOA Estimation Algorithm for Sparse Representation Under Non-Stationary Noise[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 116-121.

参考文献

[1] 吴晨曦, 张旻, 王可人. 非均匀噪声背景下的欠定DOA估计方法[J]. 系统工程与电子技术, 2018, 40(3):498-503. Wu Chenxi, Zhang Min, Wang Keren. Underdetermined direction of arrival estimation with nonuniform noise[J]. Systems Engineering and Electronics, 2018, 40(3):498-503.
[2] Liu Aijun, Li Fen, Li Bo, et al. Spatial polarimetric time-frequency distribution based DOA estimation:combining ESPRIT with MUSIC[J]. EURASIP Journal on Wireless Communications and Networking, 2018:51.
[3] Liu Song, Zhang Gang, Weng Mingjiang, et al. Unified ESPRIT spatial spectrum for direction-of-arrival estimation with an arbitrary sparse array[C]//2016 IEEE 13th International Conference on Signal Processing (ICSP). New York:IEEE Press, 2016:457-461.
[4] 陈明建, 胡振彪, 黄中瑞. 空间非平稳噪声下的宽带DOA估计算法[J]. 现代雷达, 2018, 40(1):36-42. Chen Mingjian, Hu Zhenbiao, Huang Zhongrui. Direction of arrival estimation of wideband signals with sensor arrays in spatial non-stationary noise[J]. Modern Radar, 2018, 40(1):36-42.
[5] Qi Chongying, Chen Zhijie, Wang Yongliang, et al. DOA estimation for coherent sources in unknown nonuniform noise fields[J]. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3):1195-1204.
[6] 吴云韬, 廖桂生, 张光斌. 空间非平稳噪声环境下的DOA估计新算法[J]. 西安电子科技大学学报, 2003, 30(1):51-54. Wu Yuntao, Liao Guisheng, Zhang Guangbin. A novel method for estimating DOA in the presence of spatially nonstationary noise fields[J]. Journal of Xidian University, 2003, 30(1):51-54.
[7] 汪弟杰, 王敏. 一种加性色噪声下的DOA估计新算法[J]. 广东通信技术, 2016, 36(1):28-31. Wang Dijie, Wang Min. A noval DOA estimation algorithms in additive colored noise[J]. Guangdong Communication Technology, 2016, 36(1):28-31.
[8] Liao Bin, Huang Lei, Guo Chongtao, et al. New approaches to direction-of-arrival estimation with sensor arrays in unknown nonuniform noise[J]. IEEE Sensors Journal, 2016, 16(24):8982-8989.
[9] 王洪雁, 房云飞, 裴炳南. 利用空间平滑的协方差秩最小化DOA估计方法[J]. 西安电子科技大学学报, 2018, 45(5):128-135. Wang Hongyan, Fang Yunfei, Pei Bingnan. Method for estimation of covariance rank minimization DOA by exploiting spatial smoothing[J]. Journal of Xidian University, 2018, 45(5):128-135.
[10] Malioutov D, Cetin M, Willsky A S. A sparse signal reconstruction perspective for source localization with sensor arrays[J]. IEEE Transactions on Signal Processing, 2005, 53(8):3010-3022.
[11] Zhao Wenqiang, Li Gang, Zheng Chundi, et al. Capon cepstrum weighted l2, 1 minimization for wideband DOA estimation with sonar arrays[C]//OCEANS 2016-Shanghai. New York:IEEE Press, 2016:1-4.
[12] 赵季红, 马兆恬, 曲桦, 等. 基于加权l范数稀疏信号重建的DOA估计[J]. 北京邮电大学学报, 2016, 39(5):33-36, 66. Zhao Jihong, Ma Zhaotian, Qu Hua, et al. DOA estimation based on sparse signal recovery utilizing weight l Norm[J]. Journal of Beijing University of Posts and Telecommunications, 2016, 39(5):33-36, 66.
[13] Liu Guohong, Sun Xiaoying. Two-stage matrix differencing algorithm for mixed far-field and near-field sources classification and localization[J]. IEEE Sensors Journal, 2014, 14(6):1957-1965.
[14] 刘国红. 远近场混合源定位参量估计算法研究[D]. 长春:吉林大学, 2015.

非平稳噪声下稀疏表示的DOA估计算法

DOA Estimation Algorithm for Sparse Representation Under Non-Stationary Noise

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

编辑推荐

Metrics

本文评价

[1]	李民政曹宇青颜娟娟陆健. 多智能反射面辅助毫米波级联信道估计方法[J]. 北京邮电大学学报, 2023, 46(4): 15-20.
[2]	赵地, 邓中亮, 任晓飞. 定向性天线阵列相位中心对DOA估计的影响分析[J]. 北京邮电大学学报, 2019, 42(4): 15-23.
[3]	李枝灵, 李凯, 岳晓果, 亓峰, 陈兴渝. 一种基于L₁范数的目标源测向算法[J]. 北京邮电大学学报, 2017, 40(s1): 103-107.
[4]	赵培焱, 秦记东, 彭华峰, 欧海. 基于稀疏重构的窄带弱信号时延估计算法[J]. 北京邮电大学学报, 2017, 40(5): 106-109.
[5]	赵季红, 马兆恬, 曲桦, 王伟华, 李雷雷. 基于加权1范数稀疏信号重建的DoA估计[J]. 北京邮电大学学报, 2016, 39(5): 33-36,66.
[6]	董阳阳, 赵国庆, 刘松杨. 基于L阵的低计算复杂度二维波达方向估计[J]. 北京邮电大学学报, 2016, 39(2): 20-24.
[7]	刁鸣, 安春莲. 冲击噪声背景下的DOA估计新方法[J]. 北京邮电大学学报, 2013, 36(5): 99-104.
[8]	郭艳，刘学亮，李宁,吴启辉. 适于相干信号DOA估计的改进矩阵差分方法[J]. 北京邮电大学学报, 2011, 34(2): 122-125.