A Strong Maneuvering Target-Tracking Filtering Based on Intelligent Algorithm

In this paper, a variable-structure multimodel (VSMM) filtering algorithm based on the long short-term memory (LSTM) regression-deep Q network (L-DQN) is proposed to accurately track strong maneuvering targets. The algorithm can map the selection of the model set to the selection of the action label...

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Bibliographic Details
Published in:International journal of aerospace engineering 2024-01, Vol.2024, p.1-9
Main Authors: Li, Jing, Liang, Xinru, Yuan, Shengzhi, Li, Haiyan, Gao, Changsheng
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Decision making
Error compensation
Filtration
Liquor
Maneuvering targets
Markov analysis
Neural networks
Tracking
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Summary:In this paper, a variable-structure multimodel (VSMM) filtering algorithm based on the long short-term memory (LSTM) regression-deep Q network (L-DQN) is proposed to accurately track strong maneuvering targets. The algorithm can map the selection of the model set to the selection of the action label and realize the purpose of a deep reinforcement-learning agent to replace the model switching in the traditional VSMM algorithm by reasonably designing a reward function, state space, and network structure. At the same time, the algorithm introduces a LSTM algorithm, which can compensate the error of tracking results based on model history information. The simulation results show that compared with the traditional VSMM algorithm, the proposed algorithm can quickly capture the maneuvering of the target, the response time is short, the calculation accuracy is significantly improved, and the range of adaptation is wider. Precise tracking of maneuvering targets was achieved.
ISSN:1687-5966
1687-5974
DOI:10.1155/2024/9981332