By Topic

Comparative convergence analysis of EM and SAGE algorithms in DOA estimation

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

2 Author(s)
Pei Jung Chung ; Dept. of Electr. Eng. & Inf. Sci., Ruhr-Univ. Bochum, Germany ; Böhme, Johann F.

In this work, the convergence rates of direction of arrival (DOA) estimates using the expectation-maximization (EM) and space alternating generalized EM (SAGE) algorithms are investigated. The EM algorithm is a well-known iterative method for locating modes of a likelihood function and is characterized by simple implementation and stability. Unfortunately, the slow convergence associated with EM makes it less attractive for practical applications. The SAGE algorithm proposed by Fessler and Hero (1994), based on the same idea of data augmentation, has the potential to speed up convergence and preserves the advantage of simple implementation. We study both algorithms within the framework of array processing. Theoretical analysis shows that SAGE has faster convergence speed than EM under certain conditions on observed and augmented information matrices. The analytical results are supported by numerical simulations carried out over a wide range of signal-to-noise ratios (SNRs) and various source locations

Published in:

Signal Processing, IEEE Transactions on  (Volume:49 ,  Issue: 12 )