Direct data fusion using the PMHT

Author

Rago, Constantino ; Willett, Rago Peter ; Streit, Roy

Author_Institution

Connecticut Univ., Storrs, CT, USA

Volume

3

fYear

1995

fDate

21-23 Jun 1995

Firstpage

1698

Abstract

We analyze the tracking characteristics of a new data-association/tracking algorithm proposed by Streit-Luginbuhl, the probabilistic multi-hypothesis tracking (PMHT) algorithm, in a multisensor environment. Given that in the formulation of the algorithm there is no constraint on the number of measurements originated per target, it is a natural candidate for direct fusion in the multi-sensor case, where a combined frame (assuming synchronicity among the sensors) may have more than one target-originated measurement. In this paper we compare the performance of this new algorithm to that of a commonly used multisensor tracking algorithm: the joint probabilistic data association filter with a centralized estimation-to-estimation fusion

Keywords

filtering theory; probability; sensor fusion; target tracking; tracking; centralized estimation-to-estimation fusion; direct data fusion; joint probabilistic data association filter; multisensor environment; multisensor tracking; probabilistic multi-hypothesis tracking; synchronicity; target-originated measurement; Algorithm design and analysis; Constraint optimization; Filters; Maximum a posteriori estimation; Maximum likelihood estimation; Optimization methods; Sensor fusion; Sensor phenomena and characterization; Target tracking; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, Proceedings of the 1995

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2445-5

Type

conf

DOI

10.1109/ACC.1995.529798

Filename

529798