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Modulation Signal Recognition of Underwater Acoustic Communication Based on Archimedes Optimization Algorithm and
Maofa Wang1,2, Zhenjing Zhu1,2, Gaofeng Qian1,2
1School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China.
Sensors (Basel, Switzerland)
|March 11, 2023
Summary
This study introduces an Archimedes Optimization Algorithm (AOA) and Random Forest (RF) classifier for underwater acoustic communication signal modulation recognition. The novel method achieves high accuracy, reaching 95% at signal-to-noise ratios above -5dB.
Area of Science:
- Underwater Acoustic Communication
- Signal Processing
- Machine Learning
Background:
- Noncooperative underwater communication relies on accurate modulation signal recognition.
- Traditional signal classifiers require improvement in accuracy and recognition effects.
Purpose of the Study:
- To enhance the accuracy and effectiveness of underwater acoustic communication signal modulation recognition.
- To propose a novel classifier combining the Archimedes Optimization Algorithm (AOA) and Random Forest (RF).
Main Methods:
- Selected seven different types of underwater acoustic signals for recognition.
- Extracted 11 feature parameters from the selected signals.
- Utilized the Archimedes Optimization Algorithm (AOA) to optimize Random Forest (RF) parameters (decision tree and depth).
Main Results:
- The optimized Random Forest classifier achieved high recognition accuracy for underwater acoustic communication signal modulation modes.
- Recognition accuracy reached 95% when the signal-to-noise ratio (SNR) was higher than -5dB.
- The proposed method demonstrated superior accuracy and stability compared to other classification and recognition methods.
Conclusions:
- The AOA-optimized RF classifier effectively recognizes underwater acoustic communication signal modulation modes.
- The proposed method offers a significant improvement in recognition accuracy and stability for noncooperative underwater communication.
- This approach provides a robust solution for critical applications in underwater acoustic environments.
