By Topic

Sensor-array calibration using a maximum-likelihood approach

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)
Boon Chong Ng ; Dept. of Electr. Eng., Stanford Univ., CA, USA ; See, Chong Meng Samson

High-resolution array processing algorithms for source localization are known to be sensitive to errors in the model for the sensor-array spatial response. In particular, unknown gain, phase, and mutual coupling as well as errors in the sensor positions can seriously degrade the performances of array-processing algorithms. This paper describes a calibration algorithm that estimates the calibration matrix consisting of the unknown gain, phase, and mutual-coupling coefficients as well as the sensor positions using a set of calibration sources in known locations. The estimation of the various parameters is based on a maximum likelihood approach. Cramer-Rao lower-bound (CRB) expressions for the sensor positions and the calibration matrix parameters are also derived. Numerical results are shown to illustrate the potential usefulness of the proposed calibration algorithm toward better accuracy and resolution in parametric array-processing algorithms

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:44 ,  Issue: 6 )