A novel adaptive Kalman filtering algorithm
Dian Long Guo, Yisong Dai · 2002
A simple algorithm to solve the Kalman filtering problem by using time series analysis technique is proposed. The algorithm consists of two parts. First, the parameters are estimated. Secondly, the value of the filtering is obtained based on the estimated parameters and the current measurement. To illustrated the efficiency of the algorithm, some signals, such as speech, sine-wave, and autoregressive model signals, are used to evaluate the performance of the adaptive Kalman filtering method at different signal-to-noise ratio conditions.>