A maneuvering target tracking based on fastIMM-extended Viterbi algorithm.
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| Title: | A maneuvering target tracking based on fastIMM-extended Viterbi algorithm. |
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| Authors: | Di, Yi1,2 (AUTHOR), Li, Ruiheng1,2,3 (AUTHOR) liruiheng@cqu.edu.cn, Tian, Hao1,2 (AUTHOR), Guo, Jia1,2 (AUTHOR), Shi, Binghua1,2 (AUTHOR), Wang, Zheng1,2 (AUTHOR), Yan, Ke4 (AUTHOR), Liu, Yueheng5 (AUTHOR) |
| Source: | Neural Computing & Applications. Apr2025, Vol. 37 Issue 12, p7925-7934. 10p. |
| Subjects: | Acoustic arrays, Viterbi decoding, Artificial intelligence, Image processing, Algorithms |
| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 09410643 |
| DOI: | 10.1007/s00521-023-09039-1 |
