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Proceedings Paper

Equivalent velocity tracking model for estimation of target maneuvers and design of neural network-based tracking algorithms
Author(s): Yee Chin Wong; Malur K. Sundareshan
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Paper Abstract

Selection of an appropriate dynamical model for approximating the target motion during a maneuver is critical to the design of the state estimator that reliably performs tracking of a target executing complex maneuvers. Due to the diversity in the possible maneuvers that could be executed, a number of different models may need to be included in the design of a satisfactory tracking algorithm, with corresponding increase in implementation complexity. A novel target motion model, termed Equivalent Velocity Tracking Model (EVTM), is proposed in this paper which is capable of providing good approximations to target motions during different types of maneuvers. The design of a target racking architecture that utilizes the EVTM and employs a neural network-assisted Kalman filter is outlined. Quantitative results form several tracking experiments are provided to illustrate the performance benefits resulting from the use of EVTM in the design, and are also compared with the performance resulting from other algorithms based on traditional models and multiple model approaches.

Paper Details

Date Published: 3 September 1998
PDF: 15 pages
Proc. SPIE 3373, Signal and Data Processing of Small Targets 1998, (3 September 1998); doi: 10.1117/12.324617
Show Author Affiliations
Yee Chin Wong, Univ. of Arizona (United States)
Malur K. Sundareshan, Univ. of Arizona (United States)


Published in SPIE Proceedings Vol. 3373:
Signal and Data Processing of Small Targets 1998
Oliver E. Drummond, Editor(s)

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