一种用于水下小尺度运动阵列的目标波达方向估计方法

doi:10.3969/j.issn.1000-1093.2017.09.015

兵工学报 ›› 2017, Vol. 38 ›› Issue (9): 1779-1785.doi: 10.3969/j.issn.1000-1093.2017.09.015

一种用于水下小尺度运动阵列的目标波达方向估计方法

郭拓，王英民，张立琛

（西北工业大学航海学院，陕西西安 710072）

收稿日期:2017-01-17 修回日期:2017-01-17 上线日期:2017-11-03
通讯作者: 王英民（1963—），男，教授，博士生导师 E-mail:ywang@nwpu.edu.cn
作者简介:郭拓（1986—），男，博士研究生。E-mail:guotuonwpu@126.com
基金资助:
国家自然科学基金项目(61401362)

Novel Target Direction-of-arrival Estimation Method for Underwater Small-scale Moving Array

GUO Tuo, WANG Ying-min, ZHANG Li-chen

(School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, China)

Received:2017-01-17 Revised:2017-01-17 Online:2017-11-03

摘要/Abstract

摘要： 为解决水下小尺度运动阵列对目标定位的孔径和样本不足问题，采用合成孔径方法实现孔径的扩展。通过分析相干信源情况下不同阵元数与样本数之比时样本协方差矩阵的谱分离特性，提出采用小快拍的主特征空间目标波达方向估计方法。研究结果表明：仿真实验中，阵元数与样本数之比为5时，该方法依然可以正确分辨4个目标；水池试验中，阵元数与样本数之比为4.8时，该方法同样可以准确分辨3个相邻目标。该方法不需要先验信息如信源个数等，解决了小尺度运动阵列在实际应用时所暴露的孔径和样本方面的固有局限，可满足实际应用需求。

关键词: 声学, 小尺度运动阵, 主特征空间, 波达方向估计, 小快拍

Abstract: The underwater small-scale moving array is limited by its small aperture and sample size for direction of arrival (DOA) estimation of coherent target. The passive synthetic aperture technique is used to solve the problem of insufficient aperture. The spectral separation of sample covariance matrix is stu-died in the case of coherent target. A DOA estimation method for coherent target based on main feature space is proposed, which uses small snapshots. In the simulation, the proposed method can still distinguish the four targets correctly when the ratio of the number of sensors to the number of samples is 5; in the water tank experiment, the above ratio is 4.8, and it can identify three adjacent targets clearly. The proposed method can achieve better resolution for coherent targets in small samples, which meets the application needs of small-scale motions array of targeting, and requires no priori information of signal source number.Key

Key words: acoustics, small-scalemovingarray, mainfeaturespace, DOAestimation, smallsnapshot

中图分类号:

TB566

郭拓，王英民，张立琛. 一种用于水下小尺度运动阵列的目标波达方向估计方法[J]. 兵工学报, 2017, 38(9): 1779-1785.

GUO Tuo, WANG Ying-min, ZHANG Li-chen. Novel Target Direction-of-arrival Estimation Method for Underwater Small-scale Moving Array[J]. Acta Armamentarii, 2017, 38(9): 1779-1785.

参考文献

［1］ Krim H, Viberg M. Two decades of array signal processing research: the parametric approach[J]. IEEE Signal Processing Magazine, 1996, 13(4):67-94.
[2］吴振, 戴继生, 朱湘临, 等. 互耦效应下一种基于实值稀疏表示的波达方向估计算法[J]. 兵工学报, 2015, 36(2):294-298.
WU Zhen,DAI Ji-sheng, ZHU Xiang-lin, et al. A real-valued sparse representation method for DOA estimation with unknown mutual coupling[J]. Acta Armamentarii, 2015, 36(2):294-298.(in Chinese)
[3］邹吉武, 孙大军. 线阵双基地声纳波束零点形成MUSIC算法[J]. 兵工学报, 2010, 31(3):364-368.
ZOU Ji-wu, SUN Da-jun. MUSIC algorithm of beam null forming on linear array of bi-static sonar[J]. Acta Armamentarii, 2010, 31(3):364-368.(in Chinese)
[4］王永良, 陈辉, 彭应宁, 等. 空间谱估计理论与算法[M]. 北京:清华大学出版社, 2004:2-5.
WANG Yong-liang, CHEN Hui, PENG Ying-ning, et al. Theory and algorithm of spatial spectrum estimation[M]. Beijing: Tsinghua University Press, 2004:2-5.(in Chinese)
[5］ Carlson B D. Covariance matrix estimation errors and diagonal loading in adaptive arrays[J]. IEEE Transactions on Aerospace Electronic Systems, 1988, 24(4):397-401.
[6］ Chen Y, Wiesel A, Eldar Y C, et al. Shrinkage algorithms for MMSE covariance estimation[J]. IEEE Transactions on Signal Processing, 2010, 58(10):5016-5029.
[7］ Tong J, Schreier P J, Guo Q, et al. Shrinkage of covariance matrices for linear signal estimation using cross-validation[J]. IEEE Transactions on Signal Processing, 2016, 64(11):2965-2975.
[8］ Auguin N, Morales-Jimenez D, Mckay M, et al. Robust shrinkage M-estimators of large covariance matrices[C]∥Proceedings of 2016 IEEE Statistical Signal Processing Workshop. Palma de Mallorca, Baleares, Spain:IEEE, 2016:1-4.
[9］ Pillai S U, Kwon B H. Forward/backward spatial smoothing techniques for coherent signal identification[J]. IEEE Transactions on Acoustics Speech & Signal Processing, 1989, 37(1):8-15.

[10］ Pal P, Vaidyanathan P P. A novel array structure for directions-of-arrival estimation with increased degrees of freedom[C]∥Proceedings of 2010 IEEE International Conference on Acoustics Speech and Signal Processing. Dallas, TX, US:IEEE, 2010:2606-2609.
[11］ Gershman A B, Bohme J F. Improved DOA estimation via pseudo-random resampling of spatial spectrum[J]. IEEE Signal Processing Letters, 1997, 4(2):54-57.
[12］ Vasylyshyn V. Removing the outliers in root-MUSIC via pseudo-noise resampling and conventional beamformer[J]. Signal Processing, 2013, 93(12):3423-3429.
[13］ Qian C, Huang L, So H C. Improved unitary root-MUSIC for DOA estimation based on pseudo-noise resampling[J]. IEEE Signal Processing Letters, 2014, 21(2):140-144.
[14］ Shaghaghi M, Vorobyov S A. Subspace leakage analysis and improved DOA estimation with small sample size[J]. IEEE Tran-sactions on Signal Processing, 2015, 63(12):3251-3265.
[15］ Bai Z D, Silverstein J W. No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices[J]. Annals of Probability, 1998, 26(1):316-345.
[16］ Bai Z D, Silverstein J W. Exact separation of eigenvalues of large dimensional sample covariance matrices[J]. Annals of Probability, 1999, 27(3):1536-1555.
[17］李华, 白志东, 肖玉山. 大维随机矩阵的渐进特征[J]. 东北师大学报:自然科学版, 2014, 46(4):1-8.
LI Hua, BAI Zhi-dong, XIAO Yu-shan. The asymptotic properties of the large dimension random matrix[J]. Journal of Northeast Normal University:Natural Science Edition, 2014, 46(4): 1-8.(in Chinese)
[18］ Mestre X, Lagunas M . Modified subspace algorithms for DoA estimation with large arrays[J]. IEEE Transactions on Signal Processing, 2008, 56(2): 598-614.
[19］ Stergiopoulos S, Sullivan E J. Extended towed array processing by an overlap correlator[J]. Journal of the Acoustical Society of America, 1989, 86(1): 158-171.

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一种用于水下小尺度运动阵列的目标波达方向估计方法

Novel Target Direction-of-arrival Estimation Method for Underwater Small-scale Moving Array

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