Bayesian array signal processing in additive generalized Gaussian noise

被引：0
|
作者：
Kannan, B [1 ]
机构：
[1] Natl Univ Singapore, Ctr Wireless Commun, Singapore 11764, Singapore
来源：
2001 IEEE WORKSHOP ON STATISTICAL SIGNAL PROCESSING PROCEEDINGS | 2001年
关键词：
non-Gaussian signal processing; sensor array processing; Bayesian estimation; M-H algorithm;
D O I：
10.1109/SSP.2001.955228
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present a Bayesian approach for DOA and frequency estimation of narrow band signals in additive generalized Gaussian noise. Using Bayesian techniques, the posterior probability densities for DOA (Direction Of Arrival) and frequency parameters are derived from the signal and noise models. These posterior probabilities are then used in the Metropolis-Hastings (M-H) algorithm to derive the samples for the DOA and frequency parameters. The performances of our algorithms are studied by plotting the MSEs (Mean Square Errors) of the parameters for various SNRs. The MSEs of the parameters are compared with the CRLBs (Cramer Rao Lower Bound) for the generalized Gaussian models.
引用
收藏
页码：86 / 89
页数：4
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