Title
Bayesian Complex Amplitude Estimation and Adaptive Matched Filter Detection in Low-Rank Interference
Document Type
Article
Publication Date
3-2007
Journal or Book Title
IEEE Transactions on Signal Processing
Volume
55
Issue
32
First Page
1176
Last Page
1182
DOI
10.1109/TSP.2006.887151
Abstract
We propose a Bayesian method for complex amplitude estimation in low-rank interference. We assume that the received signal follows the generalized multivariate analysis of variance (GMANOVA) patterned-mean structure and is corrupted by low-rank spatially correlated interference and white noise. An iterated conditional modes (ICM) algorithm is developed for estimating the unknown complex signal amplitudes and interference and noise parameters. We also discuss initialization of the ICM algorithm and propose a (non-Bayesian) adaptive-matched-filter (AMF) signal detector that utilizes the ICM estimation results. Numerical simulations demonstrate the performance of the proposed methods
Rights
© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Copyright Owner
IEEE
Copyright Date
2007
Language
en
File Format
application/pdf
Recommended Citation
Dogandžić, Aleksandar and Zhang, Benhong, "Bayesian Complex Amplitude Estimation and Adaptive Matched Filter Detection in Low-Rank Interference" (2007). Electrical and Computer Engineering Publications. 7.
https://lib.dr.iastate.edu/ece_pubs/7
Comments
This is a post-print of an article from IEEE Transactions on Signal Processing 55 (2007): 1176–1182, doi:10.1109/TSP.2006.887151. Posted with permission.