Adaptive Variable Structure Interacting Multiple Model Tracking Algorithm for Hypersonic Glide Vehicle
During the penetration process of hypersonic glide vehicles (HGV), the maneuvering forms are varied, which brings some challenges for tracking them, such as difficulty in the stable matching of single-model tracking and the slow response of multi-model tracking. Therefore, this paper proposes an im...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Instituto de Aeronáutica e Espaço (IAE)
2025-01-01
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| Series: | Journal of Aerospace Technology and Management |
| Subjects: | |
| Online Access: | https://jatm.com.br/jatm/article/view/1355 |
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| Summary: | During the penetration process of hypersonic glide vehicles (HGV), the maneuvering forms are varied, which brings some challenges for tracking them, such as difficulty in the stable matching of single-model tracking and the slow response of multi-model tracking. Therefore, this paper proposes an improved adaptive variable structure interacting multiple model tracking algorithm by analyzing the maneuvering characteristics of the target. The algorithm can switch between interacting multiple models and single-model tracking by defining a set of model-switching conditions. Additionally, it designs two correction functions and embeds them into the model probability update phase of the adaptive variable structure interacting multiple model algorithm, so that the proposed adaptive variable structure interacting multiple model algorithm can adaptively adjust the transition probability matrix (TPM) according to the probability law of the target maneuver model. Finally, the effectiveness and superiority of the proposed algorithm were verified through comparative simulation experiments with existing algorithms. Compared with the single-model tracking algorithm, the proposed algorithm’s position root mean square error is significantly reduced by nearly one-third, while also reducing the single running time by nearly one-fourth compared to other multi-model tracking algorithms.
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| ISSN: | 2175-9146 |