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| Implementation Technique and Validation of Target Intention Recognition Under Interference Based on Intelligent Algorithms |
| SHI Bingzheng1，2 |
| 1. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China；
2. Key Laboratory of Automatic Target Recognition （Shanghai）， Shanghai 201109， China |
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Abstract To address the core issues of traditional incoming target intention recognition methods, including reliance on hand-crafted rules, weak anti-interference capability, and poor multi-scenario adaptability, this paper proposes an incoming target intention recognition scheme based on intelligent algorithms. Firstly, a multi-dimensional input framework covering target attributes, kinematic features, and electromagnetic features is constructed. Secondly, the scenario adaptability of mainstream intelligent algorithms is comparatively analyzed, with emphasis on designing a lightweight improved Transformer model that employs a multimodal attention mechanism to enhance key feature weighting and integrates depthwise separable convolution to reduce computational complexity. Finally, experimental validation is conducted based on an air defense system simulation dataset. Results demonstrate that the improved model achieves an intention recognition accuracy of 91.8% in complex electromagnetic interference environments, representing an improvement of 17.5% over conventional support vector machines (SVM), with recognition latency controlled within 0.7 s. The model satisfies the real-time performance and robustness requirements of combat scenarios, providing technical support for the engineering application of intelligent defense systems.
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Received: 03 March 2026
Published: 04 August 2026
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2026, Vol. 9 
