基于协方差矩阵高阶幂的二维DOA估计新算法

doi:CNKI:11-1929/V.20111209.1725.004

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基于协方差矩阵高阶幂的二维DOA估计新算法

罗争^1,2, 张旻^1,2, 李鹏飞^1,2

1. 合肥电子工程学院 309研究室,安徽合肥 230037;
2. 安徽省电子制约技术重点实验室,安徽合肥 230037

收稿日期:2011-07-05 修回日期:2011-11-02 出版日期:2012-04-25 发布日期:2012-04-20
通讯作者: 张旻 E-mail:dyzhangmin@163.com
基金资助:
国家自然科学基金(60972161)

A Novel 2D DOA Estimation Algorithm Based on High-order Power of Covariance Matrix

LUO Zheng^1,2, ZHANG Min^1,2, LI Pengfei^1,2

1. Division 309, Hefei Electronic Engineering Institute, Hefei 230037, China;
2. Key Laboratory of Electronic Restricting Technology of Anhui Province, Hefei 230037, China

Received:2011-07-05 Revised:2011-11-02 Online:2012-04-25 Published:2012-04-20

摘要/Abstract

摘要： 针对稀疏分解方法进行均匀圆阵(UCA)的二维波达方向(DOA)估计运算复杂度大的问题,提出了一种基于协方差矩阵高阶幂稀疏分解的二维DOA估计新算法。该算法首先利用协方差矩阵高阶幂无需进行特征值分解和信源数估计的特性,构建了协方差矩阵高阶幂的稀疏分解向量;然后运用粒度分层思想,构造了粗区域估计和细方位估计的分层多粒度的快速分解模型,分层字典的长度大大减少,在保持估计精度的前提下,算法运算时间远小于现有的恒定冗余字典的稀疏分解方法,从而解决了基于稀疏分解的圆阵二维DOA估计问题。论文提出的算法与二维MUSIC算法相比,估计精度高,且能满足对相干信号的估计。仿真结果验证了算法的有效性和可行性。

关键词: 均匀圆阵, 二维波达方向估计, 稀疏分解, 协方差矩阵, 高阶幂, 粒度

Abstract: To reduce the computational complexity in the sparse decomposition of 2D direction of arrival (DOA) estimation based on uniform circular arrays (UCAs), a novel 2D DOA estimation algorithm using sparse decomposition of higher-order power of covariance matrix was proposed. First, this method avoids the estimation of the number of signals and eigen-value decompsition through using the high-order power of a covariance matrix as the vector of sparse decomposition. Then a fast region direction detection decomposition algorithm based on the hierarchical granularity model is put forward. This new method can construct a redundant dictionary adaptively based on the distribution of space signals, thus reducing the computational load greatly while still maintaining high estimation accuracy. Compared with the 2D MUSIC method,this algorithm not only provides better 2D DOA performance but also possesses the capability of estimating coherent signals. Simulation results confirm its effectiveness and feasibility.

Key words: uniform circular array, two-dimensional direction of arrival estimation, sparse decomposition, covariance matrix, high order power, granularity

中图分类号:

罗争, 张旻, 李鹏飞. 基于协方差矩阵高阶幂的二维DOA估计新算法[J]. 航空学报, 2012, (4): 696-704.

LUO Zheng, ZHANG Min, LI Pengfei. A Novel 2D DOA Estimation Algorithm Based on High-order Power of Covariance Matrix[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, (4): 696-704.

参考文献

[1] Hyder M M, Mahata K. Direction-of-arrival estimation using a mixed l_2,0 norm approximation. IEEE Transactions on Signal Processing, 2010, 58(9): 4646-4655.
[2] Chen F J, Kwong S, Kok C. ESPRIT-like two-dimensional DOA estimation for coherent signals. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(3): 1477-1484.
[3] Liang J L, Liu D. Joint elevation and azimuth direction finding using L-shaped array. IEEE Transactions on Antennas and Propagation, 2010, 58(6): 2136-2141.
[4] Blunt S D, Chan T, Gerlach K. Robust DOA estimation: the reiterative superresolution (RISR) algorithm. IEEE Transactions on Aerospace and Electronic Systems, 2011, 47(1): 332-346.
[5] Pan J, Zhou J J, Wang F. 2-D DOA estimation for sparse uniform circular array in presence of unknown nonuniform noise. Acta Aeronautica et Astronautica Sinica, 2011, 32(3): 448-456. (in Chinese) 潘捷, 周建江, 汪飞. 非均匀噪声稀疏均匀圆阵的二维DOA估计. 航空学报, 2011, 32(3): 448-456.
[6] Wang B H, Hui H T, Leong M S. Decoupled 2D direction of arrival estimation using compact uniform circular arrays in the presence of elevation-dependent mutual coupling. IEEE Transactions on Aerospace and Electronic Systems, 2010, 58(3): 747-755.
[7] Yang X Y, Chen B X. A high resolution method for 2D DOA estimation. Journal of Electronics & Information Technology, 2010, 32(4): 953-958. (in Chinese) 杨雪亚,陈伯孝. 一种新的二维角度估计的高分辨算法. 电子与信息学报, 2010, 32(4): 953-958.
[8] Fonseca N, Coudyser M, Laurin J J, et al. On the design of a compact neural network-based DOA estimation system. IEEE Transactions on Antennas and Propagation, 2010, 58(2): 357-366.
[9] Zhang M, Li P F. A broadband direction of arrival (DOA) estimation approach based on hierarchy neural networks. Journal of Electronics & Information Technology, 2009, 31(9): 2118-2122. (in Chinese) 张旻, 李鹏飞. 基于分层神经网络的宽频段DOA 估计方法. 电子与信息学报, 2009, 31(9): 2118-2122.
[10] Zhang M, Li P F. Direction of arrival estimation approach based on phase angle feature of correlation function using RBF neural networks. Journal of Electronics & Information Technology, 2009, 31(12): 2926-2930. (in Chinese) 张旻, 李鹏飞. 基于互相关函数相角特征的RBF神经网络来波方位估计. 电子与信息学报, 2009, 31(12): 2926-2930.
[11] El Zooghby A H, Christodoulou C G, Georgiopoulos M. A neural network-based smart antenna for multiple source tracking. IEEE Transactions on Antennas Propagation, 2000, 48(5): 768-775.
[12] Zhang S, Li Y M, Song J C. A novel method for DOA estimation based on generalized-prior distribution. 2010 International Conference on Measuring Technology and Mechatronics Automation. 2010: 244-247.
[13] Malioutov D, Cetin M, Willsky A S. A sparse signal reconstruction perspective for source localization with sensor arrays. IEEE Transactions on Signal Processing, 2005, 53(8): 3010-3022.
[14] Guo X S, Wan Q, Chang C Q, et al. Source localization using a sparse representation framework to achieve super resolution. Mulitidimensional Systems and Signal Processing, 2010, 21(4): 391-402.
[15] Tang Z J, Blacquière G, Leus G. Aliasing-free wideband beamforming using sparse signal representation. IEEE Transactions on Signal Processing, 2011, 59(7): 3464-3469.
[16] Liu Z M, Huang Z T, Zhou Y Y. Direction-of-arrival estimation of wideband signals via covariance matrix sparse representation. IEEE Transactions on Signal Processing, 2011, 59(9): 4256-4270.
[17] Yin J H, Chen T Q. Direction-of-arrival estimation using a sparse representation of array covariance vectors. IEEE Transactions on Signal Processing, 2011, 59(9): 4489-4493.
[18] Goossens R, Rogier H. A hybrid UCA-RARE/root-MUSIC approach for 2-D direction of arrival estimation in uniform circular arrays in the presence of mutual coupling. IEEE Transactions on Antennas and Propagation, 2007, 55(3): 841-849.
[19] Elad M, Bruckstein A M. A generalized uncertainty principle and sparse representation in pairs of bases. IEEE Transactions on Information Theory, 2002, 48(9): 2558-2567.
[20] Malioutov D, Çetin M, Willsky A S. A sparse signal reconstruction perspective for source localization with sensor arrays. IEEE Transactions on Signal Processing, 2005, 53(8): 3010-3022.
[21] Peng Q L, Si X C, Li L. Fast subspace DOA algorithm without eigendecomposition. Systems Engineering and Electronics, 2010, 32(4): 691-693. (in Chinese) 彭巧乐, 司锡才, 李利. 一种无特征分解的快速子空间DOA算法. 系统工程与电子技术, 2010, 32(4): 691-693.
[22] Donoho D L, Huo X. Uncertainty principles and ideal atomic decompositions. IEEE Transactions on Information Theory, 2001, 47(7): 2845-2862.
[23] Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit. SIAM Review, 2001, 43(1): 129-159.
[24] Park Y H, Pasricha S, Kurdahi F J, et al. A multi-granularity power modeling methodology for embedded processors. IEEE Transactions on Very Scale Integration (VLSI) Systems, 2011, 19(4): 668-681.
[25] Qian Y H, Liang J Y, Wu W Z, et al. Information granularity in fuzzy binary GrC model. IEEE Transactions on Fuzzy Systems, 2011, 19(2): 253-264.
[26] Pedrycz W, Song M L. Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity. IEEE Transactions on Fuzzy Systems, 2011, 19(3): 527-539.

E-mail：hkxb@buaa.edu.cn

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主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于协方差矩阵高阶幂的二维DOA估计新算法

A Novel 2D DOA Estimation Algorithm Based on High-order Power of Covariance Matrix

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