A comparison of several different approaches for target tracking with clutter

Author

Pao, Lucy Y. ; Powers, Richard M.

Author_Institution

Dept. of Electr. & Comput. Eng., Colorado Univ., Boulder, CO, USA

Volume

5

fYear

2003

fDate

4-6 June 2003

Firstpage

3919

Abstract

Five different methods suitable for tracking single targets in clutter are compared: the nearest neighbor algorithm, the probabilistic multi-hypothesis tracking filter, the probabilistic data association filter, the mixture reduction algorithm, and the mean-field event-averaged maximum likelihood estimator. Across a range of clutter densities, comparison results were generated for a common, fixed set of Monte Carlo target, target measurement, and clutter measurement realizations. The relative performances, as measured by track lifetime, RMS tracking error, and computational complexity are compared.

Keywords

Monte Carlo methods; clutter; computational complexity; maximum likelihood estimation; target tracking; tracking filters; Monte Carlo target realization; RMS tracking error; clutter; clutter densities; clutter measurement realization; computational complexity; mean-field event-averaged maximum likelihood estimator; mixture reduction algorithm; nearest neighbor algorithm; probabilistic data association filter; probabilistic multihypothesis tracking filter; target measurement realization; target tracking; track lifetime; Clutter; Density measurement; Filters; Maximum likelihood detection; Maximum likelihood estimation; Nearest neighbor searches; Neural networks; Performance evaluation; Target tracking; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 2003. Proceedings of the 2003

ISSN

0743-1619

Print_ISBN

0-7803-7896-2

Type

conf

DOI

10.1109/ACC.2003.1240448

Filename

1240448