Robust Algorithm for Sensor Position Estimation Against the Direction Deviations of the Calibration Sources
Ding Wang · Dianzi xuebao · 2013
The direction deviations of the calibration sources would seriously degrade the calibration precision of the sen- sor positions.Aiming to this problem, the robust calibration algorithm for estimating the sensor shape against the location devi- ations is presented under the condition that the prior probability distribution of the direction deviations is available.The robust algorithm is derived based on the signal subspace fitting( SSF) technique and the Bayesian estimation theory frame, and it is numerically implemented via the Newton iteration without optimizing the locations of the calibration sources.Both the theory analysis and simulation experiments validate that the novel algorithm has preferable robustness against the location deviations of the calibration sources and its asymptotic performance can reach the Cramer-Rao bound( CRB) under some moderate conditions.