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

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.

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

Language

en

File Format

application/pdf

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