By Topic

Estimation of DOA in unknown noise: performance analysis of UN-MUSIC and UN-CLE, and the optimality of CCD

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)
Qiang Wu ; Commun. Res. Lab., McMaster Univ., Hamilton, Ont., Canada ; Kon Max Wong

In a previous paper, a new approach was proposed for the consistent estimation of the directions of arrival (DOA) of signals in an unknown spatially correlated noise environment using generalized correlation decomposition (GCD). Based on the various interesting properties of the eigenspace structure obtained by GCD, two effective methods (UN-MUSIC and UNCLE) of estimating the DOA in an unknown correlated noise were developed, In this paper, the performance of the two methods are analyzed. It is shown that the performance of these two methods can be optimized by assigning optimum weighting matrices in their respective criteria. Furthermore, and more importantly, it is also shown that of all the correlation decompositions, the canonical correlation decomposition (CCD) leads to the optimum performance of the methods. Computer simulations confirm these conclusions and show that the use of CCD is robust even under variable spatially correlated noise conditions

Published in:

Signal Processing, IEEE Transactions on  (Volume:43 ,  Issue: 2 )