00000cab a22000003a 4500 UP-99796217611094738 Buklod 20231008001307.0 m |o d | ta 140128s xx d | ||r ||||| || DENGII eng Du, Xiongjie Robust sensor bias estimation for ill-conditioned scenarios. June 2012 p.319-323 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. Data fusion. Sensor bias estimation. Wang, Yue. Shan, Xiuming. Tsinghua Science and Technology 17, 3 (June 2012). FO UPD DENG-II Article