Estimation for the Linear Model With Uncertain Covariance Matrices

被引:4
作者
Zachariah, Dave [1 ]
Shariati, Nafiseh [1 ]
Bengtsson, Mats [1 ]
Jansson, Magnus [1 ]
Chatterjee, Saikat [1 ]
机构
[1] KTH Royal Inst Technol, ACCESS Linnaeus Ctr, S-10044 Stockholm, Sweden
基金
瑞典研究理事会; 欧洲研究理事会;
关键词
Maximum a posteriori estimation; covariance matrices; inverse Wishart; ROBUST ESTIMATION; SIGNAL; NOISE;
D O I
10.1109/TSP.2014.2301973
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We derive a maximum a posteriori estimator for the linear observation model, where the signal and noise covariance matrices are both uncertain. The uncertainties are treated probabilistically by modeling the covariance matrices with prior inverse-Wishart distributions. The nonconvex problem of jointly estimating the signal of interest and the covariance matrices is tackled by a computationally efficient fixed-point iteration as well as an approximate variational Bayes solution. The statistical performance of estimators is compared numerically to state-of-the-art estimators from the literature and shown to perform favorably.
引用
收藏
页码:1525 / 1535
页数:11
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