A kind of incremental Kalman smoother under poor observation condition
Xiaojun Sun, Guangming Yan, Bo Zhang · 2017
When the observation equation of system has not been verified or corrected under certain environmental conditions, applying it will yield to unknown system errors and filtering errors. In this paper, a kind of incremental Kalman smoothing algorithm is presented, which can eliminate the unknown system errors and improve the accuracy of state estimators. This algorithm is simple in form and easy to be applied in engineering practice. The simulation results show its effectiveness and feasibility.