Design and implementation of intent inference for airborne multifunctional radar based on LSTM

Hongbin Jin; Xin Wang; Mingyue Feng; Peng Yang

doi:10.1117/12.3031050

19 July 2024 Design and implementation of intent inference for airborne multifunctional radar based on LSTM

Hongbin Jin, Xin Wang, Mingyue Feng, Peng Yang

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131812I (2024) https://doi.org/10.1117/12.3031050
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

In order to infer the behavioral intention of airborne multifunctional radar, a working mode transformation model was studied, and an intention inference algorithm was designed based on LSTM. A pattern transformation simulation dataset was constructed, and the intention inference practice of airborne multifunctional radar was carried out. The research results indicate that time length and batch processing rate have a significant impact on the final prediction results. When the timing length is set to 60 and the batch processing rate is set to 20, the prediction accuracy can mostly be maintained above 85%, which lays an important foundation for determining combat actions and countermeasures in actual combat.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongbin Jin, Xin Wang, Mingyue Feng, and Peng Yang "Design and implementation of intent inference for airborne multifunctional radar based on LSTM", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131812I (19 July 2024); https://doi.org/10.1117/12.3031050

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