Equivalent velocity tracking model for estimation of target maneuvers and design of neural network-based tracking algorithms
Yee Chin Wong, Malur K. Sundareshan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
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.