4.7 Article

A Study of Endpoint-Constrained Nonlinear Tracking Filters

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAES.2021.3090919

Keywords

Target tracking; Mathematical model; Trajectory; Filtering algorithms; Kalman filters; Aerodynamics; Predictive models; Constrained Kalman filter; endpoint constraint; extended Kalman filter (EKF); interacting multiple-model (IMM); particle filtering; target tracking; unscented Kalman filter (UKF)

Funding

  1. JHUAPL

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This article introduces a new filter that combines a modified version of the EPC with a multiple-model algorithm to achieve superior performance against a wider range of ASCM trajectories than the EPC EKF.
The development and performance of an endpoint-constrained (EPC) extended Kalman filter (EKF) were published by Haug and Ford, where the EPC EKF was shown to outperform similar non-EPC EKFs against highly maneuverable antiship cruise missile (ASCM) trajectories. The purpose of this article is to resolve two issues identified during the original study. The first issue is that EKFs may not offer superior performance when the target's motion is highly nonlinear. The second issue is that the EPC EKF performs poorly against the high diver trajectory, where the target does not satisfy the EPC until the dive begins. This article presents a new filter that uses a modified version of the EPC and a multiple-model algorithm to achieve superior performance against a larger set of ASCM trajectories than the EPC EKF.

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