Enhanced Tracking of Ballistic Targets Using Forward Looking Infrared Measurements
Abstract
This thesis is an extension of earlier work performed at AFIT towards tracking airborne targets using FLIR measurements. The research has aimed at replacing a standard correlation tracker with a hybrid Kalman filter/enhanced correlation tracker for implementation in a high energy laser weapon. In this thesis the target trajectory being tracked is modelled as a benign, non- maneuvering, thrusting ballistic missile trajectory at large sensor-to-target ranges. To capture the characteristic shape of the exhaust plume, the plume is modelled as the difference between two bivariate Gaussian functions with elliptical equal intensity contours. As the missile ascends on its thrusting trajectory, the exhaust plume tends to oscillate (pogo) along the direction of the velocity vector. In this thesis, a second-order Gauss-Markov process is used to model the plume's 'pogo' oscillation properties. The ultimate goal is to design a multiple model adaptive filter (MMAF) algorithm composed of elemental filters tuned for varying plume pogo parameters (frequency and amplitude characteristics). This MMAF accounts for atmospheric disturbance effects of the propagating infrared wave fronts, as well as bending/vibrational effects of the optical hardware associated with the FLIR sensor. The bank of filters provide the accurate estimation capability to guide the pointing mechanism of a shared aperture laser/FLIR sensor. Keywords: Infrared tracking correlation algorithms, Guided missile tracking, Laser tracking, Kalman filtering.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1989
- Accession Number
- ADA205727
Entities
People
- David R. Rizzo
Organizations
- Air Force Institute of Technology