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基于Light Reverse Transformer的空中目标意图识别方法
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V219; TP183

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国家自然科学基金(62002362,61703426);陕西省高校科协青年人才托举计划(2019038);陕西省创新能力支持计划(2020KJXX-065


A Method of Recognizing Air Target Intent Based on Light Reverse Transformer
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    摘要:

    空中目标意图识别在战场态势感知领域占据举足轻重的地位。然而,如何从海量态势数据中迅速且精准地挖掘关键信息,一直是该领域研究面临的一大难题。现有多数研究模型因架构繁复,难以在短时间内高效地推断出目标意图。为解决这一难题,基于Transformer架构进行设计,通过Reverse方法优化模型以更适用于处理时间序列任务,并在位置编码中融入扰动元素,以提升模型的鲁棒性和泛化能力。此外,对注意力机制和前馈神经网络进行了轻量化改进。经过对比实验、消融实验以及计算复杂度的深入分析,所提模型在空中目标意图识别领域的有效性得到了有力验证。

    Abstract:

    Recognition of air target intent occupies a position of strategic importance in the realm of battlefield situational awareness. Nonetheless, how to quickly and accurately extract pertinent information from extensive situational data is still a question in this domain. The majority of prevalent research models are characterized by intricate architectures, hindering the efficient inference of target intentions within a concise timeframe. For the above-mentioned reasons, a model is introduced based on Transformer architecture. The model is optimized by Reverse method to adapt it further to handle time-series tasks. And, the integration of perturbation elements merged into the position encoding elevates the model’s robustness and generalization capabilities. Additionally, this paper implements lightweight enhancements to both the attention mechanism and the feedforward neural network. By a comprehensive evaluation encompassing comparative experiments, ablation studies, and an in-depth analysis of computational complexity, the efficacy of the proposed model is unequivocally substantiated within the domain of airborne target intent recognition.

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王科, 郭相科, 王亚男, 倪鹏, 权文, 李成海.基于Light Reverse Transformer的空中目标意图识别方法[J].空军工程大学学报,2025,26(3):96-105

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  • 在线发布日期: 2025-06-04
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