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Robust sensor bias estimation for ill-conditioned scenarios

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3 Author(s)
Du, Xiongjie ; Department of Electronic Engineering, Tsinghua University, Beijing 100084, China ; Wang, Yue ; Shan, Xiuming

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.

Published in:

Tsinghua Science and Technology  (Volume:17 ,  Issue: 3 )