Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

Multitarget tracking with the von Mises-Fisher filter and probabilistic data association (CROSBI ID 226684)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Marković, Ivan ; Bukal, Mario ; Ćesić, Josip ; Petrović, Ivan Multitarget tracking with the von Mises-Fisher filter and probabilistic data association // Journal of advances in information fusion, 11 (2016), 2; 157-172

Podaci o odgovornosti

Marković, Ivan ; Bukal, Mario ; Ćesić, Josip ; Petrović, Ivan

engleski

Multitarget tracking with the von Mises-Fisher filter and probabilistic data association

Directional data emerge in many scientific disciplines due to the nature of the observed phenomena or the working principles of a sensor. The problem of tracking with direction- only sensors is challenging since the motion of the target typically resides either in 3D or 2D Euclidean space, while the corresponding measurements reside either on the unit sphere or the unit circle, respectively. Furthermore, in multitarget tracking there is the need to deal with the problem of pairing sensors measurements with targets in the presence of clutter (the data association problem). In this paper we propose to approach multitarget tracking in clutter with direction-only data by setting it on the unit hypersphere, thus tracking the objects with a Bayesian estimator based on the von Mises-Fisher distribution and probabilistic data association. To achieve this goal we derive the probabilistic data association (PDA) filter and the joint probabilistic data association (JPDA) filter for the Bayesian von Mises-Fisher estimation on the unit hypersphere. The final PDA and JPDA filter equations are derived with respect to the Kullback-Leibler divergence by preserving the first moment of the hyperspherical distribution. Although the fundamental equations are given for the hyperspherical case, we focus on the filters on the unit 1- sphere (circle in R^2) and the unit 2-sphere (surface of the unit ball in R^3). The proposed approach is validated through synthetic data experiments on 100 Monte Carlo runs simulating multitarget tracking with noisy directional measurements and clutter.

von Mises-Fisher distribution ; Multitarget tracking ; Probabilistic data association

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o izdanju

11 (2)

2016.

157-172

objavljeno

1557-6418

Povezanost rada

Elektrotehnika, Računarstvo, Temeljne tehničke znanosti

Indeksiranost