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Improvement of a Green's Function Estimation for a Moving Source Using the Waveguide Invariant Theory.
Daehwan Kim1, Donghyeon Kim2, Gihoon Byun3
1Department of Ocean Engineering, Korea Maritime and Ocean University, Busan 49112, Republic of Korea.
Sensors (Basel, Switzerland)
|September 14, 2024
Summary
This study improves underwater sound channel characterization by enhancing the signal-to-noise ratio of broadband Green's functions. The new method uses waveguide invariant and ray-based blind deconvolution for moving sources in shallow water.
Area of Science:
- Ocean acoustics
- Signal processing
- Remote sensing
Background:
- Underwater sound channel characterization is vital for remote sensing.
- Traditional methods for estimating channel impulse response (CIR) are computationally intensive.
- Ray-based blind deconvolution (RBD) is a less demanding alternative but struggles with noise.
Purpose of the Study:
- To introduce a novel method for improving the signal-to-noise ratio (SNR) of broadband Green's functions.
- To enable accurate estimation for moving sources without prior range knowledge.
- To overcome noise limitations in traditional RBD techniques.
Main Methods:
- Utilizing the waveguide invariant to enhance SNR.
- Applying RBD with plane-wave beamforming to estimate Green's functions.
- Coherently combining Green's functions at adjacent ranges using frequency shifts from striation slopes.
Main Results:
- Significantly improved SNR of broadband Green's functions.
- Successful demonstration via simulation and real-world shallow water noise data.
- Effective characterization of underwater sound channels for moving sources.
Conclusions:
- The proposed method effectively improves Green's function estimation in noisy underwater environments.
- Waveguide invariant and RBD offer a robust approach for underwater acoustic channel characterization.
- This technique advances remote sensing applications by providing more reliable acoustic data.
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