[1]褚鼎立,陈红,蔡晓霞.基于盖尔圆准则的信源数目估计改进算法[J].探测与控制学报,2018,40(04):109.[doi:.]
 CHU Dingli,CHEN Hong,CAI Xiaoxia.An Improved Source Number Estimation Algorithm Based on Geschgorin Disk Estimator Criterion[J].,2018,40(04):109.[doi:.]
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基于盖尔圆准则的信源数目估计改进算法()
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《探测与控制学报》[ISSN:1008-1194/CN:61-1316/TJ]

卷:
40
期数:
2018年04期
页码:
109
栏目:
出版日期:
2018-08-26

文章信息/Info

Title:
An Improved Source Number Estimation Algorithm Based on Geschgorin Disk Estimator Criterion
文章编号:
1008-1194(2018)04-0109-07
作者:
褚鼎立陈红蔡晓霞
国防科技大学电子对抗学院, 安徽 合肥 230037
Author(s):
CHU Dingli CHEN Hong CAI Xiaoxia
Electronic Countermeasure Institute of National University of Defense Technology,Hefei 230037, China
关键词:
盲源分离信源数目估计最小信息准则盖尔圆准则
Keywords:
blind sources separation(BSS) source number estimation Akaike information criterion (AIC) Geschgorin disk estimator (GDE)
分类号:
TN911.7
DOI:
.
文献标志码:
A
摘要:
针对最小信息准则(Akaike Information Criterion,AIC)存在的非渐进一致性估计的缺陷,以及盖尔圆准则(Gerschgorin Disk Estimator,GDE)可能出现无序特征值导致检测错误的问题,提出了一种基于盖尔圆准则和最小信息准则的GDE-AIC信源数目估计算法。该算法利用盖尔圆半径与噪声模型无关的特性构造似然函数,将其引入AIC准则模型中,克服了AIC准则非渐进一致性估计的缺点,且适用于空间色噪声的环境。在仿真实验中,将该算法与AIC算法及GDE算法等进行对比,结果表明,该方法稳定性好,适用于白噪声与色噪声,且在低信噪比时仍具有良好的估计性能。
Abstract:
Aiming at the defect that non-asymptotic consistency estimation of Akaike Information Criterion (AIC) exists and the Gerschgorin Disk Estimator (GDE) may lead to detection errors caused by disorder eigenvalues, a GDE-AIC source number estimation algorithm based on Gerschgorin Disk Estimator (GDE) and Minimum Information Criterion (AIC) was proposed. This algorithm constructed the likelihood function because the Gail circle radius was independent of the noise model to, which was introduced into the AIC criterion model and overcomes the shortcomings of AIC criterion non-gradual consistency estimation for space color noise environment. In the simulation experiment, the algorithm was compared with AIC algorithm and GDE algorithm. Simulation results showed that the proposed method was stable and suitable for white noise and color noise in comparison with AIC algorithm and GDE algorithm,which still had good estimation performance at low SNR.

参考文献/References:

[1]Choi S, Cichocki A, Adaptive blind separation of speech signals: cocktail party problem. International Conference on Speech Processing, Seoul, 1997, 617-622.
[2]Wax M, Kailath T. Detection of signals by information theoretic criteria[J].IEEE Trans on Acoustics Speech and Signal Processing, 1985, 33(2): 387-392.
[3]Wang Rongjie, Zhan Yiju. A Method of dynamic DOA estimation with an unknown number of sources[C]//IEEE International Conference on Mechatronics and Automation. US: IEEE, 2015: 104-109.
[4]张洪渊, 贾鹏, 史习智. 确定盲分离中未知信号源个数的奇异值分解法[J]. 上海交通大学学报(自然科学版), 2001, 35(8): 1155-1158.
[5]NADLER B. Nonparametric detection of signals by information theoretic criteria: Performance analysis and an improved estimator[J].IEEE Transactions on Signal Processing, 2010, 58(5): 2746-2756.
[6]HUANG L, LONG T, WU SJ. Source enumeration for high-resolution array processing using improved Gerschgorin radii without eigendecomposition[J].IEEE Transzctions on Signal Processing, 2008, 56(12): 5916-5925.
[7]Akaike H. A new look at the statistical model identification[J]. Automatic Control IEEE Transactions on, 1974, 19(6): 716-723.
[8]Schwarz G. Estimating the dimension of a model[J]. Annals of Statistics, 1978, 6(2):15-18.
[9]Rissanen J. Modeling by shortest data description[J]. Automatica, 1978, 14(5): 465-471.
[10]Wu H T, Yang J F, Chen F K. Source number estimators using transformed Gerschgorin radii[J]. Signal Processing IEEE Transactions on, 1995, 43(6): 1325-1333.
[11]许佳奇, 王川川, 曾勇虎,等. 盖尔圆定理和最小描述长度准则相结合的信源数目估计方法研究[J]. 信号处理, 2017,33(S1): 53-57.

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备注/Memo

备注/Memo:
收稿日期:2018-01-22
作者简介:褚鼎立(1993—),男,山东烟台人,硕士研究生,研究方向:盲源分离。E-mail: 1240699100@qq.com
更新日期/Last Update: 2018-09-14