Von Mises Mixture PHD Filter (CROSBI ID 220742)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Marković, Ivan ; Ćesić, Josip ; Petrović, Ivan
engleski
Von Mises Mixture PHD Filter
This paper deals with the problem of tracking multiple targets on the unit circle, a problem that arises whenever the state and the sensor measurements are circular, i.e. angular-only, random variables. To tackle this problem, we propose a novel mixture approximation of the probability hypothesis density filter based on the von Mises distribution, thus constructing a method that globally captures the non-Euclidean nature of the state and the measurement space. We derive a closed-form recursion of the filter and apply principled approximations where necessary. We compared the performance of the proposed filter with the Gaussian mixture probability hypothesis density filter on a synthetic dataset of 100 randomly generated multitarget trajectory examples corrupted with noise and clutter, and on the PETS2009 dataset. We achieved respectively a decrease of 10.5% and 2.8% in the optimal subpattern assignement metric (notably 16.9% and 10.8% in the localization component).
von Mises distribution; probability hypothesis density filter; multitarget tracking; directional statistics
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Podaci o izdanju
22 (12)
2015.
2229-2233
objavljeno
1070-9908
10.1109/LSP.2015.2472962
Povezanost rada
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti