Date of Award

12-17-2004

Degree Type

Thesis

Degree Name

M.S.

Degree Program

Engineering

Department

Electrical Engineering

Major Professor

Li, X. Rong

Second Advisor

Chen, Huimin

Third Advisor

Jilkov, Vesselin

Abstract

There are many multiple-model (MM) target-tracking algorithms that are available but there has yet to be a comparison that includes all of them. This work compares seven of the currently most popular MM algorithms in terms of performance, credibility, and computational complexity. The algorithms to be considered are the autonomous multiple-model algorithm, generalized pseudo- Bayesian of first order, generalized pseudo-Bayesian of second order, interacting multiple-model algorithm, B-Best algorithm, Viterbi algorithm, and reweighted interacting multiple-model algorithm. The algorithms were compared using three scenarios consisting of maneuvers that were both in and out of the model set. Based on this comparison, there is no clear-cut best algorithm but the B-best algorithm performs best in terms of tracking errors and the IMM algorithm has the best computational complexity among the algorithms that have acceptable tracking errors.

Rights

The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.

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