Acoustic modulation signal recognition based on endpoint detection

Li Xiuquan ¹, Wang Zhen ², Jin Yeyin ³

⁰Hangzhou Institute of Computer External Equipment, Hangzhou, China.

Scientific Reports +

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August 19, 2024

View abstract on PubMed

Summary

This study introduces an optimized acoustic modulation recognition algorithm for signal demodulation and reconnaissance. The enhanced method achieves over 99% accuracy in distinguishing complex signals like 2FSK and 4FSK.

Area Of Science

Signal Processing
Communications Engineering
Acoustic Signal Analysis

Background

Modulation recognition is vital for signal demodulation and communication reconnaissance.
Acoustic signals (under 20 kHz) present unique challenges for accurate identification.

Purpose Of The Study

To investigate and enhance modulation recognition technology for acoustic signals.
To improve signal preprocessing and feature extraction techniques for better accuracy.

Main Methods

Compared four endpoint detection algorithms for modulation signal recognition.
Optimized the short-time energy entropy ratio algorithm with three noise reduction methods.
Enhanced cyclic spectrum analysis using kurtosis coefficient for differentiating 2FSK and 4FSK signals.

Main Results

The optimized algorithm demonstrated effective modulation recognition capabilities.
Achieved over 99% recognition accuracy for differentiating 2FSK and 4FSK signals at a 4 dB SNR.
Successful noise reduction and feature extraction were confirmed.

Conclusions

The proposed acoustic modulation recognition algorithm significantly improves signal identification accuracy.
The optimized cyclic spectrum analysis is effective for distinguishing similar frequency shift keying signals.
This research contributes to advancements in signal demodulation and reconnaissance technologies.

Keywords:

Communication technology Cyclic spectrum parameters Endpoint detection Modulation recognition