Kinematic and Static Filtering for Multi-Sensor Navigation Systems
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Abstract
An efficient signal fusion method is put forward for the integrated navigation of the multiple sensor system.To show the correlations of the master filter and the local filters,the covariance matrix among the local filter outputs and that of the local filter and master filter outputs are presented.In order to avoid the correlations between the fusion data sets of the multiple sensors,a synthetic Kalman filtering composed by a kinematic Kalman filtering step and several static Kalman filtering steps is presented.The new developed robust Kalman filtering and the adaptively robust Kalman filtering can be easily extended in this kind of synthetic filtering.
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