Title :
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
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;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
