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A Novel Single-Station Tracking Algorithm towards High-Dynamic Targets in 3D Space

Published: 18 April 2024 Publication History

Abstract

Single-station target tracking is a technology that uses only one observation station to track the moving targets. At present, the target motion model of most single-station tracking algorithms is the constant velocity model, which is not suitable for high-dynamic targets. In this paper, a high-dynamic target tracking algorithm based on Unscented Kalman Filter (UKF) is proposed. Firstly, the 2D-MUSIC algorithm is used to estimate the azimuth and pitch angles of the target relative to the observation station. Then the time stamp information is used to obtain the propagation delay. Finally, the UKF algorithm is used to estimate the position, velocity and acceleration of the target. Simulation results show that the proposed algorithm can achieve higher estimation accuracy for the target state than the Extended Kalman Filter (EKF) algorithm and the UKF algorithm without acceleration estimation.

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      ICCNS '23: Proceedings of the 2023 13th International Conference on Communication and Network Security
      December 2023
      363 pages
      ISBN:9798400707964
      DOI:10.1145/3638782
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 18 April 2024

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      Author Tags

      1. angle of arrival (AOA)
      2. high dynamic
      3. single-station tracking
      4. time of arrival (TOA)
      5. unscented Kalman filter(UKF)

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