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Proceedings Paper

Fundamentals of on-road tracking
Author(s): Robert H. Enders
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Paper Abstract

Among the various ways in which ground targets differ from air-targets, a most important one is that in order to travel substantial distances, ground targets generally need to move on roads. Alpha-beta type filters or Kalman filters, i.e., tracking filters designed for air-targets, have not dealt with constrained target motion. The use of road-constraints changes both the prediction and update steps in the tracing problem. In this paper a Bayesian framework is developed, in which the road information, in standard vector-product form, is incorporated with the predicted target location into the Bayesian prior. Both the maximum a posterior and Bayes least-squares solutions are then computed. An examination of the results shows that the MAP solutions is potentially unstable when two conditions coincide: the target is located near a road bend and the sensors return is located inside the bend. Because of this potential instability, the preferred update solution turns out to be the along-road average of the updated location probability density. Formulas for calculating or effectively approximately the solution and its along-road variance are given, as well as an association measure for multi-target tracking, track initiation, and clutter rejection by gating.

Paper Details

Date Published: 15 July 1999
PDF: 9 pages
Proc. SPIE 3692, Acquisition, Tracking, and Pointing XIII, (15 July 1999); doi: 10.1117/12.352875
Show Author Affiliations
Robert H. Enders, MITRE Corp. (United States)


Published in SPIE Proceedings Vol. 3692:
Acquisition, Tracking, and Pointing XIII
Michael K. Masten; Larry A. Stockum, Editor(s)

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