Nicholas D. Assimakis
Kalman Filter Gain Elimination in Linear Estimation
236 - 241
2020
14
7
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10011301
https://publications.waset.org/vol/163
World Academy of Science, Engineering and Technology
In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the ndimensional state vector using the mdimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.
Open Science Index 163, 2020