Track Fusion Fractional Kalman Filter

Compared with the integer order system model, the fractional order system model can describe the actual system more accurately, so it can achieve higher accuracy of state estimation. In this paper, a track fusion fractional order Kalman filter is proposed for multi-sensor fractional order system with uncorrelated noise, which can effectively improve the state estimation accuracy of multi-sensor fractional order system. The algorithm is simple, the amount of calculation is small, and it is convenient for engineering application. Simulation results show the effectiveness and feasibility of the proposed algorithm.