By Topic

Sensor array calibration using measured steering vectors of uncertain location

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

3 Author(s)
See, Chong-Meng Samson ; Defence Sci. Organ., Singapore ; Boon-Kiat Poh ; Cowan, C.F.N.

We present a maximum likelihood approach for calibrating sensor arrays in the presence of mutual coupling, channel gain and phase mismatch and array geometry uncertainties using measured steering vectors of uncertain locations. The estimated perturbation parameters is used to calibrate the array manifold, hence enabling many high resolution array processing algorithms to attain their potential advantages. We present two methods for optimizing the highly nonlinear and multimodal ML cost function. The first method is a linearized local gradient search algorithm. The second method is derived from combining the fast local search of gradient methods with the nonlinear global search ability of the genetic algorithm. The resulting hybrid optimizer is both fast and globally converging. Simulation results are presented to illustrate the usefulness of the proposed approach

Published in:

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on  (Volume:5 )

Date of Conference:

21-24 Apr 1997