Multi-sensor optimal weighted fusion incremental Kalman smoother

Abstract

In practical applications, the system observation error is widespread. If the observation equation of the system has not been verified or corrected under certain environmental conditions, the unknown system errors and filtering errors will come into being. The incremental observation equation is derived, which can eliminate the unknown observation errors effectively. Furthermore, an incremental Kalman smoother is presented. Moreover, a weighted measurement fusion incremental Kalman smoother applying the globally optimal weighted measurement fusion algorithm is given. The simulation results show their effectiveness and feasibility.