Complex-Valued Gaussian Sum Filter for Nonlinear Filtering of Non-Gaussian/Non-Circular Noise

被引:22
|
作者
Mohammadi, Arash [1 ]
Plataniotis, Konstantinos N. [1 ]
机构
[1] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON M5S 3G4, Canada
关键词
Gaussian-sum filter; improper complex Gaussian signals; non-Gaussian noise; nonlinear systems; WIDELY LINEAR-ESTIMATION; TARGET TRACKING; IMPULSIVE NOISE; RECEIVERS; SYSTEMS;
D O I
10.1109/LSP.2014.2361459
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
Motivated by application of Gaussian sum filters (GSF) and multiple model adaptive estimation (MMAE) approaches in scenarios where assumption of proper (circular) Gaussian signals is not valid, the letter proposes a novel complex-valued Gaussian sum filter (C/GSF) for non-linear filtering of non-Gaussian/non-circular measurement noise. Although the literature on recursive state estimation using GSF is rich, its complex-valued counterpart which incorporates the full second-order statistics of the system and can cope with non-Gaussian/non-circular-measurements, has not yet been investigated in the literature. The paper addresses this gap. The C/GSF is a computationally attractive adaptive filter where the number of non-circular Gaussian components is controlled utilizing a modified Bayesian learning technique which is used to collapse the resulting non-Gaussian sum mixture into an equivalent complex-valued Gaussian term. Simulation results indicate that the C/GSF provides significant performance improvement over its traditional counterparts.
引用
收藏
页码:440 / 444
页数:5
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