Cart (Loading....) | Create Account
Close category search window
 

A Max-Search Approach for DOA Estimation With Unknown Number of Signals

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Pei-Jung Chung ; Inst. for Digital Commun., Univ. of Edinburgh, Edinburgh, UK

We present a novel max-search approach for maximum-likelihood (ML) DOA estimation with unknown number of signals. Conventional methods such as the information theoretic criterion-based approach and the multiple hypothesis test procedure estimate the model order and parameters of interest simultaneously. These methods are usually computationally expensive since ML estimates are required for a series of nested models. In this paper, we propose a computationally efficient solution to avoid this full search procedure. Our method computes ML estimates for the maximally hypothesized model, and selects relevant estimates associated with true parameters by thresholding likelihood ratios. Furthermore, we derive an upper bound and a lower bound on the error covariance matrix. Numerical results show that despite model order uncertainty, the max-search procedure yields comparable estimation accuracy as standard approaches at a much reduced computational cost.

Published in:

Selected Topics in Signal Processing, IEEE Journal of  (Volume:4 ,  Issue: 3 )

Date of Publication:

June 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.