Title :
Linear-time JPDAF based on many-2-many approximation of marginal association probabilities
Author_Institution :
Dept. of Inf., Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany
Abstract :
A novel linear-time approximation for the marginal association probabilities in the JPDAF is proposed. The key idea is to combine two existing approximations that are based on (computationally cheap) many-2-1 and 1-2-many association models. Simulations demonstrate the benefits of the novel approximation, called many-2-many approximation, in comparison with existing linear-time approaches.
Keywords :
approximation theory; filtering theory; object tracking; probability; sensor fusion; 1-2-many association model; joint probabilistic data association filter; linear-time JPDAF; linear-time approximation; many-2-1 association model; many-2-many approximation; marginal association probabilities; measurement-to-object association; object tracking;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2015.1411
