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Proceedings Paper

Measurement-based neural net multitarget tracker
Author(s): Mark Yee
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Paper Abstract

A neural network solution to the data association problem in multitarget tracking is presented. This requires position and velocity measurements of the targets over two consecutive time frames. A quadratic neural energy function results that is suitable for an optical processing implementation. Realistic target trajectories are simulated, yielding several different scenarios with spurious measurements (clutter) and measurement noise, which are used to test the tracking ability of the neural network. Simulation results are presented, and an overall tracking system using the neural net, Kalman filters, and a Hough transform subsystem is discussed.

Paper Details

Date Published: 1 October 1990
Proc. SPIE 1305, Signal and Data Processing of Small Targets 1990, (1 October 1990); doi: 10.1117/12.2321767
Show Author Affiliations
Mark Yee, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 1305:
Signal and Data Processing of Small Targets 1990
Oliver E. Drummond, Editor(s)

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