IM3HT algorithm: A joint formulation of IMM and MHT for multitarget tracking

Author

Torelli, R. ; Graziano, A. ; Farina, A.

Author_Institution

Dept. of Comput. Sci. & Syst., Univ. of Rome La Sapienza, Rome, Italy

fYear

1997

fDate

1-7 July 1997

Firstpage

2979

Lastpage

2984

Abstract

IMM (Interacting Multiple Model) and MHT (Multiple Hypothesis Tracking) are today interesting techniques in the tracking field. Specifically, IMM is a filtering technique where r standard filters cooperate to match the true target model; MHT is a multiscan correlation logic, which defers data association until more data are available so to reduce the risk of mis-correlation. The combination of IMM and MHT promise improved tracking performance: we shall term such algorithm as IM3HT. The paper provides a theoretical formulation of this new algorithm; also, the results of performance comparison with a "classical" MHT in terms of tracking errors are included.

Keywords

Kalman filters; filtering theory; sensor fusion; IM3HT algorithm; IMM; MHT; data association; filtering technique; interacting multiple model; multiple hypothesis tracking; multiscan correlation logic; multitarget tracking; standard filters; Acceleration; Accuracy; Adaptation models; Filtering; Filtering algorithms; Radar tracking; Target tracking; Adaptive; Estimation; Tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (ECC), 1997 European

Conference_Location

Brussels

Print_ISBN

978-3-9524269-0-6

Type

conf

Filename

7082564