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Proceedings Paper

Pursuer guidance parameter identification and time-to-go estimation using angle-only measurements from an evader
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Paper Abstract

In this paper we present an algorithm for identifying the parameters of a proportional navigation guidance missile (pursuer) pursuing an airborne target (evader) using angle-only measurements from the latter. This is done for the purpose of classifying the missile so that appropriate countermeasures can be taken. In the literature, there have been numerous studies on how a pursuer tracks an evader and what the optimal guidance law should be. However, not much has been done on identifying/classifying the pursuer from the evader's point of view using angle-only measurements. This provides the motivation for our current work. Mathematical models are constructed for a pursuer with a changing velocity, i.e., a direction change and a speed change. Assuming the pursuer is launched from the ground with an acceleration, its motion can be described by a four-dimensional parameter vector consisting of its proportional navigation constant and three parameters related to thrusting (initial net specific thrust, the relative mass ejection rate and its maximum speed). Consequently, the problem can be solved as a parameter estimation problem, rather than state estimation. In this paper, we provide an estimator based on Maximum Likelihood (ML) to solve this identification problem. The parameter estimates obtained can be mapped into the time-to-go until intercept, thus the time-to-go estimate can also be obtained from the above estimator. Estimation results are presented for different scenarios together with the Cramer-Rao Lower Bound, which quantifies the best achievable estimation accuracy. The accuracy of the time-to-go estimate is also obtained. Simulation results demonstrate that the proposed estimator is efficient by meeting the CRLB.

Paper Details

Date Published: 5 January 2004
PDF: 12 pages
Proc. SPIE 5204, Signal and Data Processing of Small Targets 2003, (5 January 2004); doi: 10.1117/12.504567
Show Author Affiliations
Lin Lin, Univ. of Connecticut (United States)
Thiagalingam Kirubarajan, McMaster Univ. (Canada)
Yaakov Bar-Shalom, Univ. of Connecticut (United States)

Published in SPIE Proceedings Vol. 5204:
Signal and Data Processing of Small Targets 2003
Oliver E. Drummond, Editor(s)

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