Title :
Multitarget tracking via joint PHD filtering and multiscan association
Author :
Papi, F. ; Battistelli, G. ; Chisci, L. ; Morrocchi, S. ; Farina, A. ; Graziano, A.
Author_Institution :
Dip. Sist. e Inf., Univ. di Firenze, Firenze, Italy
Abstract :
A PHD (probability hypothesis density) filter and multiscan association are combined in a feedback fashion in order to provide robust and efficient multitarget tracking. The resulting hybrid tracker, thanks to the feedback connection, provides remarkable performance improvements with respect to both an open-loop PHD filter with estimate extraction via clustering and a traditional tracker equipped with a track formation logic.
Keywords :
filtering theory; probability; sensor fusion; target tracking; estimate extraction; joint PHD filtering; multiscan association; multitarget tracking; probability hypothesis density filter; track formation logic; Density functional theory; Feedback; Filtering; Filters; Logic; Radar tracking; Recursive estimation; Robustness; State estimation; Target tracking; PHD filtering; Random set tracking; multiscan association; multitarget tracking;
Conference_Titel :
Information Fusion, 2009. FUSION '09. 12th International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
978-0-9824-4380-4
