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

Volume

6

fYear

1997

fDate

4-6 Jun 1997

Firstpage

3698

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;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1997. Proceedings of the 1997

Conference_Location

Albuquerque, NM

ISSN

0743-1619

Print_ISBN

0-7803-3832-4

Type

conf

DOI

10.1109/ACC.1997.609520

Filename

609520