Title
Knowledge-Aided Adaptive Coherence Estimator in Stochastic Partially Homogeneous Environments
Abstract
This letter introduces a stochastic partially homogeneous model for adaptive signal detection. In this model, the disturbance covariance matrix of training signals, , is assumed to be a random matrix with some a priori information, while the disturbance covariance matrix of the test signal, , is assumed to be equal to , i.e., . On one hand, this model extends the stochastic homogeneous model by introducing an unknown power scaling factor between the test and training signals. On the other hand, it can be considered as a generalization of the standard partially homogeneous model to the stochastic Bayesian framework, which treats the covariance matrix as a random matrix. According to the stochastic partially homogeneous model, a scale-invariant generalized likelihood ratio test (GLRT) for the adaptive signal detection is developed, which is a knowledge-aided version of the well-known adaptive coherence estimator (ACE). The resulting knowledge-aided ACE (KA-ACE) employs a colored loading step utilizing the a priori knowledge and the sample covariance matrix. Various simulation results and comparison with respect to other detectors confirm the scale-invariance and the effectiveness of the KA-ACE.
Year
DOI
Venue
2011
10.1109/LSP.2011.2107510
IEEE Signal Process. Lett.
Keywords
Field
DocType
bayesian inference,generalized likelihood ratio test,knowledge-aided,partially homogeneous model,bayesian methods,signal to noise ratio,stochastic process,stochastic processes,bayesian method,covariance matrix,detectors
Applied mathematics,Mathematical optimization,Likelihood-ratio test,Signal-to-noise ratio,A priori and a posteriori,Stochastic process,Covariance matrix,Statistics,Mathematics,Random matrix,Lambda,Estimator
Journal
Volume
Issue
ISSN
18
3
1070-9908
Citations 
PageRank 
References 
10
0.58
8
Authors
5
Name
Order
Citations
PageRank
Pu Wang11808.42
Zafer Sahinoglu245638.93
Man-On Pun372247.90
Hongbin Li413711.40
Braham Himed568657.96