Fast prediction method for dynamic RCS of rotary wing small UAVs

Yuguang Tian; Qiang Li; Gaogui Xu; Junwen Chen

doi:10.1117/12.3022661

18 March 2024 Fast prediction method for dynamic RCS of rotary wing small UAVs

Yuguang Tian, Qiang Li, Gaogui Xu, Junwen Chen

Proceedings Volume 13104, Advanced Fiber Laser Conference (AFL2023); 131041Q (2024) https://doi.org/10.1117/12.3022661
Event: Advanced Fiber Laser Conference (AFL2023), 2023, Shenzhen, China

Abstract

In the military field, studying the characteristics of radar cross section (RCS) of multi-rotor small UAVs is of great significance for UAV penetration and high-value target feature simulation. By studying the variation law of dynamic RCS of multi-rotor small UAV and combining deep learning technology, a dynamic RCS rapid estimation method based on Long Short-Term Memory (LSTM) is proposed, and its prediction effect is simulated and verified. This method can estimate the RCS of UAVs within a certain time range in the future during the flight of multi-rotor small UAVs, and provide data support for the optimal waveform design and target recognition of "low, slow and small" target detection, and then realize the accurate interception of multi-rotor small UAVs.

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

Citation Download Citation

Yuguang Tian, Qiang Li, Gaogui Xu, and Junwen Chen "Fast prediction method for dynamic RCS of rotary wing small UAVs", Proc. SPIE 13104, Advanced Fiber Laser Conference (AFL2023), 131041Q (18 March 2024); https://doi.org/10.1117/12.3022661

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