期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
卷 66, 期 7, 页码 1282-1286出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSII.2018.2878951
关键词
Linear Kalman filter; noisy control variable; discrete time state estimation
资金
- National Natural Science Foundation of China [91648208]
- National Natural Science Foundation-Shenzhen Joint Research Program [U1613219]
- Natural Science Basic Research Plan in Shaanxi Province of China [2017JM6033]
This brief focuses on the development of a linear Kalman filtering algorithm when the control input variable is corrupted by noises. The noisy input is considered in the derivation process of the Kalman filter, and an extra term is included in the covariance matrix of the one step error. A bias estimation is naturally generated by the input noise. To reduce the bias, a new cost function of the state estimation error with a regularization term is proposed to obtain the Kalman gain matrix. Simulation results in the context of discrete time state estimation demonstrate that the proposed algorithm can achieve excellent estimation performance in terms of the steady-state misalignment under noisy input environments.
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