A Novel Adaptive Filter Based on Kalman Filtering Algorithm and Its Implementation

In order to improve the performance of adaptive filter, by researching the kalman filtering algorithm, presents a novel adaptive filtering algorithm. In this paper, the proposed algorithm describes dynamic change of the filter weight using the state space. In addition, the filter output consists of measurement equation, and then, based on the above mentioned theory, the filter weights update are realized depending on Kalman filtering recursive algorithm. In order to analyze the performance of the proposed algorithm, this paper implements this algorithm using simulink simulation tool at the physical layer. Furthermore, the simulation platform for performance analysis of the proposed filter is established. Simulation results show that the proposed algorithm has better convergence and tracking performance, also confirm that its performance is better than that of conventional algorithms.