Share Email Print

Proceedings Paper

Multiple model estimator for a tightly coupled HRR automatic target recognition and MTI tracking system
Author(s): Jeffery R. Layne; David A. Simon
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The goal of this research is to exploit couplings between tracking and ATR systems employing high range resolution radar (HRRR) and moving target indicator (MTI) measurements. As will be shown, these systems are coupled via pose, kinematic, and association constraints. Exploiting these couplings results in a tightly coupled system with significantly improved performance. This problem deals with two different types of spaces, namely the continuous space kinematics (e.g. position and velocity) and the discrete space target type. A multiple model estimator (MME) was chosen for this problem. The MME consist of a bank of extended Kalman filters (one for each target type). The continuous space kinematics are dealt with via these extended Kalman filter. Further, the probability of each Kalman filter is computed and used to determine the corresponding discrete space target probability. Presented in this paper are empirical results that show improvement over conventional techniques.

Paper Details

Date Published: 13 August 1999
PDF: 12 pages
Proc. SPIE 3721, Algorithms for Synthetic Aperture Radar Imagery VI, (13 August 1999); doi: 10.1117/12.357653
Show Author Affiliations
Jeffery R. Layne, Air Force Research Lab. (United States)
David A. Simon, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 3721:
Algorithms for Synthetic Aperture Radar Imagery VI
Edmund G. Zelnio, Editor(s)

© SPIE. Terms of Use
Back to Top