Adaptive Tracking of Maneuvering Targets Based on IR Image Data,
Abstract
The capability of tracking dynamic target from forward looking infrared (FLIR) measurements has been improved substantially by replacing standard correlation trackers with adaptive extended Kalman filters or enhanced correlator/Kalman filter combinations. This research investigates a tracker able to handle multiple hot-spot targets, in which digital and/or optical signal processing is employed on the FLIR data to identify the underlying target shape. Furthermore, multiple model adaptive filtering is investigated as a means of changing the field-of-view as well as the tracker bandwidth when target acceleration can vary over a wide range. Enhancements are developed and analyzed: 1) allowing some of the elemental filters within the adaptive algorithm to have rectangular fields-of-view and to be tuned for target dynamics that are harsher in one direction than others, 2) considering both Gauss-Markov acceleration models and constant turn-rate models for target dynamics, and 3) devising an initial target acquisition algorithm to remove important biases in the estimated target template to be used within the tracker. The performance potential of such a tracking algorithm is shown to be substantial.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 04, 1989
- Accession Number
- ADP005822
Entities
People
- Peter S. Maybeck
Organizations
- Air Force Institute of Technology