INS/DVL integrated navigation is commonly used in AUV underwater navigation. The error observation value is called outliers which caused by DVL equipment error and environmental factors. The outliers decrease the stability and precision of filter seriously. To dispel the influence of the outliers, an adaptive outlier-restrained Kalman filter is presented by analyzing the characteristics and error model of low-precision integrated navigation system of AUV. Experimental results show that the adaptive outlier-restrained Kalman filter algorithm (AOKF) can improve the stability and precision of filter intensely, which has the practical value of engineering.
On SINS/DVL Integrated Navigation Based on an Adaptive Outlier-restrained Kalman Filter
01.08.2018
163216 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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