Paper
3 September 1998 Equivalent velocity tracking model for estimation of target maneuvers and design of neural network-based tracking algorithms
Yee Chin Wong, Malur K. Sundareshan
Author Affiliations +
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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yee Chin Wong and Malur K. Sundareshan "Equivalent velocity tracking model for estimation of target maneuvers and design of neural network-based tracking algorithms", Proc. SPIE 3373, Signal and Data Processing of Small Targets 1998, (3 September 1998); https://doi.org/10.1117/12.324617
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KEYWORDS
Motion models

Neural networks

Detection and tracking algorithms

Filtering (signal processing)

Algorithm development

Evolutionary algorithms

Doppler effect

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