Ship target radiated noise modulation spectrum processing: integration with deep learning methods

Lin Mu

doi:10.1117/12.3011637

7 December 2023 Ship target radiated noise modulation spectrum processing: integration with deep learning methods

Lin Mu

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129414N (2023) https://doi.org/10.1117/12.3011637
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

The modulation spectrum processing of ship target radiated noise is an important means of detecting, tracking, and recognizing targets in naval operations. Improving the processing performance of modulation spectrum is crucial for enhancing naval combat capabilities. This paper combines traditional modulation spectrum processing methods with deep learning methods and proposes a modulation spectrum feature enhancement method based on deep learning. The experimental results show that, the method can effectively improve the clarity and extraction quality of the line spectrum in the modulation spectrum time-frequency map.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lin Mu "Ship target radiated noise modulation spectrum processing: integration with deep learning methods", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129414N (7 December 2023); https://doi.org/10.1117/12.3011637

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