Kalman filter augmentation of a classically designed closed loop tracking system
The Kalman filter is one of the most widely used algorithms to be derived from the state variable techniques of modern control theory. Since the filter's inception in 1960, it has been applied to many tasks including inertial navigation, attitude alignment, and target tracking. The Kalman filter is a recursive algorithm that provides statistically based estimates of parameters and variables from numerical measurements. Its mathematical foundations and a specific application are described in this report. An evaluation of modern and classical control techniques is performed within the framework of a closed loop tracking system. The baseline classically designed controller commands a second order tracking system to maintain track of a high speed airborne target through the use of an off boresight error signal. A nine state Kalman filter designed for tracking in the Cartesian coordinate system is also used as a supplementary system to estimate the position of the target relative to the boresight. The Kalman filter system is computationally intensive and is run at a slower update rate than the baseline system to reflect this. The target to be tracked is travelling at a velocity of 250 meters per second with acceleration of 30 meters per second squared while performing a lateral turn at a range of 5000 meters. The tracking performance requirements of .25 milliradians error per channel is achieved for this airborne target by both the baseline and the Kalman filter systems. The presence of the filter does not significantly aid the tracker in minimizing angular error but allows the most highly sophisticated and accurate firing solutions to be used by a missile or gun system. The minimum error estimates of position, velocity, and acceleration in three dimensions from the filter can be used to linearly predict the location of the target at the time of interception.
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Master of Science (M.S.)
College of Engineering
Electrical Engineering and Communication Sciences
Length of Campus-only Access
Masters Thesis (Open Access)
Orlando (Main) Campus
Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic
Garrison, Charles Jeffrey, "Kalman filter augmentation of a classically designed closed loop tracking system" (1989). Retrospective Theses and Dissertations. 4139.