TY  - JOUR
AU  - Du, Xiongjie
AU  - Wang, Yue
AU  - Shan, Xiuming
PY  - 2012
TI  - Robust Sensor Bias Estimation for Ill-Conditioned Scenarios
JO  - Tsinghua Science and Technology
SN  - 1007-0214
SP  - 319
EP  - 323
VL  - 17
IS  - 3
AB  - Sensor bias estimation is an inherent problem in multi-sensor data fusion systems. Classical methods such as the Generalized Least Squares (GLS) method can have numerical problems with ill-conditioned sets which are common in practical applications. This paper describes an azimuth-GLS method that provides a solution to the ill-conditioning problem while maintaining reasonable accuracy compared with the classical GLS method. The mean square error is given for both methods as a criterion to determine when to use this azimuth-GLS method. Furthermore, the separation boundary between the azimuth-GLS favorable region and that of the GLS method is explicitly plotted. Extensive simulations show that the azimuth-GLS approach is preferable in most scenarios.
UR  - https://doi.org/10.1109/TST.2012.6216763
DO  - 10.1109/TST.2012.6216763