Robust Sensor Bias Estimation for Ill-Conditioned Scenarios |
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Authors: | Xiongjie Du Yue Wang Xiuming Shan |
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Affiliation: | Department of Electronic Engineering, Tsinghua University, Beijing 100084, China |
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Abstract: | 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. |
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Keywords: | data fusion sensor bias estimation ill-conditioning |
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