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An Efficient Compression Method of Underwater Acoustic Sensor Signals for Underwater Surveillance
Yong Guk Kim1,2, Dong Gwan Kim2, Kyucheol Kim2
1Gwangju Institute of Science and Technology, School of Electrical Engineering and Computer Science, Gwangju 61005, Korea.
Sensors (Basel, Switzerland)
|May 20, 2022
Summary
This study introduces a novel, low-complexity compression method for underwater acoustic sensor signals, crucial for efficient underwater surveillance and data management. The new technique offers significant improvements in compression ratio and processing speed.
Area of Science:
- Signal Processing
- Acoustics
- Data Compression
Background:
- Underwater surveillance relies on extensive acoustic sensor networks.
- Limited data processing and storage necessitate efficient signal compression.
- Low-complexity compression is vital for real-time underwater operations.
Purpose of the Study:
- To propose a novel, low-complexity, and nearly lossless compression method for underwater acoustic sensor signals.
- To address the challenges of data handling in underwater surveillance systems.
- To optimize compression for diverse operational environments and purposes.
Main Methods:
- Utilized quadrature mirror filter (QMF)-based sub-band splitting.
- Incorporated linear predictive coding techniques.
- Analyzed entropy coding suitable for underwater sensor data.
Main Results:
- The proposed method demonstrated superior compression ratios and processing times compared to existing lossless techniques.
- Achieved compression ratios comparable to the SHORTEN algorithm (10-bit maximum mode).
- Maintained similar average Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) indices.
Conclusions:
- The developed compression method is effective for underwater acoustic sensor signals.
- It offers a practical solution for data management in underwater surveillance.
- The method balances compression efficiency with data fidelity.
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