A maneuvering target tracking based on fastIMM-extended Viterbi algorithm

• Published in: Neural computing & applications Vol. 37; no. 12; pp. 7925 - 7934
• Main Authors: Di, Yi, Li, Ruiheng, Tian, Hao, Guo, Jia, Shi, Binghua, Wang, Zheng, Yan, Ke, Liu, Yueheng
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2025; Springer Nature B.V
• Subjects: Acoustics; Algorithms; Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Efficiency; Estimates; Image Processing and Computer Vision; Interactive multiple model tracking; Kalman filters; Kinematics; Maneuvering targets; Maneuvers; Modules; Probability and Statistics in Computer Science; Real time; S.I.:Fuzzy Logic and Probabilistic Modelling of Uncertain Information Systems; Sensors; Special Issue on Research Advances In Fuzzy Logic and Probabilistic Modelling of Uncertain Information Systems; Tracking; Viterbi algorithm detectors; Acoustic array tracking; Extended Viterbi algorithm; Fast interactive multi-model; Maneuver detection
• ISSN: 0941-0643; 1433-3058
• DOI: 10.1007/s00521-023-09039-1

A fastIMM-extended Viterbi (fastIMM-EV) algorithm-based maneuvering target tracking method is proposed for the real-time tracking of ground maneuvering targets by a ballistic acoustic array, which firstly adopts the extended Viterbi interactive multi-model (IMM-EV) algorithm to select the best model from a given model set to match the maneuvering target motion pattern; secondly, the α – β filter and α – β – γ filter are used to replace the 2D or 3D Kalman filter in the traditional IMM algorithm, respectively, to form the fastIMM-EV algorithm, which nearly improves the algorithm efficiency, and at the same time, for the switching problem of different fastIMM-EV modules, a target maneuver recognition parameter is defined as the switching factor of the fastIMM-EV module, so that fastIMM-EV to switch the module when the target maneuver occurs; finally, the MATLAB simulation test results verify the practicality and high efficiency of the algorithm in this paper compared with different IMM target tracking methods.