Title :
Interacting multiple model algorithm based on α-β/α-β-γ filters
Author :
Pan, Quan ; Liang, Yan ; Dai, Guanzhong ; Zhang, Hongcai
Author_Institution :
Dept. of Autom. Control, Northwestern Polytech. Univ., Xian, China
Abstract :
An interacting multiple model with constant filtering gain (CFG-IMM) algorithm is developed for target tracking which uses α-β and α-β-γ filters as a means for mapping the different kinetic modes. Four methods which combine IMM with α-β and α-β-γ filters at the interacting level are proposed. The simulation results show that this algorithm is not only highly accurate but also computationally efficient and robust in spite of the manoeuvring level and measurement noise level
Keywords :
Kalman filters; Monte Carlo methods; filtering theory; parameter estimation; probability; state estimation; target tracking; transfer function matrices; α-β filters; α-β-γ filters; constant filtering gain; interacting multiple model algorithm; kinetic modes; manoeuvring level; measurement noise level; target tracking; Adaptive filters; Computational efficiency; Computational modeling; Filtering algorithms; Kinetic theory; Noise level; Noise measurement; Noise robustness; Switches; Target tracking;
Conference_Titel :
American Control Conference, 1997. Proceedings of the 1997
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3832-4
DOI :
10.1109/ACC.1997.609520
