[1]王科文,谭鸽伟.未知噪声背景下的改进型MMUSIC算法[J].华侨大学学报(自然科学版),2012,33(4):388-391.[doi:10.11830/ISSN.1000-5013.2012.04.0388]
　WANG Ke-wen,TAN Ge-wei.An Improved MMUSIC Algorithm in the Presence of Unknown Noise Field[J].Journal of Huaqiao University(Natural Science),2012,33(4):388-391.[doi:10.11830/ISSN.1000-5013.2012.04.0388]
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未知噪声背景下的改进型MMUSIC算法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第33卷
期数:
2012年第4期
页码:
388-391
栏目:
出版日期:
2012-07-20

文章信息/Info

Title:
An Improved MMUSIC Algorithm in the Presence of Unknown Noise Field
文章编号:
1000-5013(2012)04-0388-04
作者:
王科文;  谭鸽伟
华侨大学 信息科学与工程学院, 福建 厦门 361021
Author(s):
WANG Ke-wen;  TAN Ge-wei
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
关键词:
波达方向;  未知噪声;  修正多重信号分类算法;  协方差差分法
Keywords:
direction of arrival;  unknown noise;  modified multiple signal classification algorithm;  covariance differencing approach
分类号:
TN911.7
DOI:
10.11830/ISSN.1000-5013.2012.04.0388
文献标志码:
A
摘要:
针对不能确知被估计信号源的相关性和非平稳且噪声功率未知的高斯噪声环境,提出一种改进型的修正多重信号分类(MMUSIC)算法.用协方差差分法消除阵列协方差矩阵中的未知噪声矩阵,再用MMUSIC算法对得到的协方差差分矩阵进行解相关或解相干处理.该算法只要求阵元数为不少于2L+1,即可在不影响相干信号源估计的同时,保证不相关信号源的估计性能.仿真结果表明:算法能够在不能确知信号源相关性和低信噪比的未知噪声环境下,对信号源进行有效的波达方向估计,获得很高的估计精度和角度分辨率.
Abstract:
Aimed at the problems of unknown the correlation of signal sources and the gauss noise environment which is nonstationary and unknown noise power, an improved modified multiple signal classification(MMUSIC)algorithm is proposed in this paper. Firstly, covariance differencing approach is used to eliminate unknown noise matrix from array covariance matrix. Then, the covariance differencing matrix is decorrelated or decoherenced by MMUSC algorithm. The algorithm only requires that the number of array elements isn’t less than 2L+1, it doesn’t affect the estimation of coherent signal sources and simultaneously ensure the estimated performance of uncorrelated signal sources. Simulation results show that the method can effectively estimate the signals’ direction of arrival(DOA)in the presence of unknown correlation of signal sources and unknown noise filed with low signal to noise ratio(SNR), and get very high estimation accuracy and angular resolution.

参考文献/References:

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[3] PAULRJA A,KAILATH T,PAULRJA A,et al.Eigen-structure methods for direction of arrival estimation in the presence of unknown noise fields[J].IEEE Trans Acoust Speech Signal Processing,1986,34(1):13-20.
[4] MOGHADDAMJOO A.Transform-based covariance differencing approach to the array with spatially non-stationary noise[J].IEEE Trans Signal Process,1991,39(1):219-221.
[5] SU Shu-jing,WANG Zeng-gang,YAN Jing-long.New method of DOA estimation for coherent sources under unknown noise field[C]//Proceedings of 9th International Conference on Electronic Measurement and Instruments.Beijing:IEEE Computer Society,2009:4569-4572.
[6] 魏凤梅.前/后向空间平滑算法与修正MUSIC算法对相关信源DOA估计性能的比较[J].电子科技,2004(8):24-28.
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[1]胡茂兵,汤炜,蔡灿辉.一种新的子空间更新算法在DOA估计中的应用[J].华侨大学学报(自然科学版),2012,33(4):375.[doi:10.11830/ISSN.1000-5013.2012.04.0375]
　HU Mao-bing,TANG Wei,CAI Can-hui.Application of a New Subspace Updating Algorithm in DOA Estimation[J].Journal of Huaqiao University(Natural Science),2012,33(4):375.[doi:10.11830/ISSN.1000-5013.2012.04.0375]

备注/Memo

备注/Memo:
收稿日期: 2011-08-15
通信作者: 谭鸽伟(1970-),女,讲师,主要从事智能天线的研究.E-mail:tangewei70@163.com.
更新日期/Last Update: 2012-07-20