Second-order statistics-based blind equalization of FIR/IIR multiple-input multiple-output channels with common zeros

1998 ◽  
Author(s):  
Jitendra K. Tugnait ◽  
Bin Huang
Keyword(s):  
Order Statistics ◽  
Multiple Input Multiple Output ◽  
Blind Equalization ◽  
Second Order ◽  
Second Order Statistics ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Common Zeros

scholarly journals An Overdispersed Black-Box Variational Bayesian–Kalman Filter with Inaccurate Noise Second-Order Statistics

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7673
Author(s):  
Lin Cao ◽  
Chuyuan Zhang ◽  
Zongmin Zhao ◽  
Dongfeng Wang ◽  
Kangning Du ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Order Statistics ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Black Box ◽  
Second Order ◽  
Second Order Statistics ◽  
Robust Kalman Filter ◽  
Input Multiple Output ◽  
Cost Of Time

Aimed at the problems in which the performance of filters derived from a hypothetical model will decline or the cost of time of the filters derived from a posterior model will increase when prior knowledge and second-order statistics of noise are uncertain, a new filter is proposed. In this paper, a Bayesian robust Kalman filter based on posterior noise statistics (KFPNS) is derived, and the recursive equations of this filter are very similar to that of the classical algorithm. Note that the posterior noise distributions are approximated by overdispersed black-box variational inference (O-BBVI). More precisely, we introduce an overdispersed distribution to push more probability density to the tails of variational distribution and incorporated the idea of importance sampling into two strategies of control variates and Rao–Blackwellization in order to reduce the variance of estimators. As a result, the convergence process will speed up. From the simulations, we can observe that the proposed filter has good performance for the model with uncertain noise. Moreover, we verify the proposed algorithm by using a practical multiple-input multiple-output (MIMO) radar system.

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