The PMHT for maneuvering targets

Author

Ruan, Yanhua ; Willett, Peter ; Streit, Roy

Author_Institution

Connecticut Univ., Storrs, CT, USA

Volume

4

fYear

1998

fDate

21-26 Jun 1998

Firstpage

2432

Abstract

Via the EM algorithm and a slight modification of the usual target-tracking assumptions, the probabilistic multi-hypothesis tracker (PMHT) of Streit and Luginbuhl (1995) combines data-association and filtering to a simple, elegant, and efficient iterative procedure. The PMHT works well; but part of its appeal is a consistent and extensible statistical foundation. In the paper we show one such extension, that designed to track maneuvering targets. The basis, as is in common with many algorithms designed for maneuvering targets, is of an underlying and hidden “model-switch” process controlled by a Markov probability structure

Keywords

Markov processes; filtering theory; probability; target tracking; Markov probability structure; data-association; expectation maximisation algorithm; filtering; iterative procedure; maneuvering targets; model-switch process; probabilistic multi-hypothesis tracker; Algorithm design and analysis; Current measurement; Filtering algorithms; Iterative algorithms; Kalman filters; Probability; Process control; Target tracking; Time measurement; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1998. Proceedings of the 1998

Conference_Location

Philadelphia, PA

ISSN

0743-1619

Print_ISBN

0-7803-4530-4

Type

conf

DOI

10.1109/ACC.1998.703070

Filename

703070