Studying the extended Kalman filter — adaptive digital filter system operation as the non-stationary signal filter

Processing the non-stationary signals of various origin in the robotic device control systems appears to be a relevant task. Introduction of the extended Kalman filter (EKF) in operation with the non-stationary signals, including their filtering, is limited by the EKF precise setting, i.e. by the observed system model and the EFK algorithm covariance matrices. It requires the algorithm adaptivity to the input noisy non-stationary signal changing rapidly. The paper proposes to filter the non-stationary signals using the EKF — adaptive digital filter (ADF) system. The system appears to be an EKF supplemented by the ADF with the NLMS (Normalized Least Mean Squares) adaptation algorithm and is introduced to compensate for the EKF operation error in filtering the non-stationary signals. Studying the EKF-ADF system operation as the non-stationary signal filter showed that with the non-stationary signal exposed to a significant noise level the RFK-ATS system algorithm, compared to the RFK algorithm with settings similar to the RFK settings in the RFK-ATS system, has the signal-to-noise ratio highest values for the filtering results. The RFK-ATS system could be introduced in observing the robotic device state, it is able to operate in the non-stationary processes.
EDN: ONANWI, https://elibrary/onanwi

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