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Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar
Jie Huang1,2,3, Tian Zhou4,5,6, Weidong Du7,8,9
1Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China. huangjie_iron_man@hrbeu.edu.cn.
Sensors (Basel, Switzerland)
|November 21, 2018
Summary
A new fast deconvolved beamforming algorithm significantly reduces computational complexity for real-time, high-resolution multibeam sonar imaging. This innovation improves topographic surveys and target distinction in acoustic imaging.
Area of Science:
- Signal Processing
- Acoustics
- Sonar Technology
Background:
- Traditional deconvolution algorithms like Richardson-Lucy (R⁻L) are computationally intensive.
- High-resolution beamforming in multibeam sonar systems requires efficient processing.
Purpose of the Study:
- To introduce a novel, computationally efficient fast deconvolved beamforming algorithm.
- To enhance the performance of high-frequency multibeam sonar systems.
Main Methods:
- Utilizing the convolution theorem and fast Fourier transform (FFT) to optimize the R⁻L algorithm.
- Applying the new algorithm to a high-frequency multibeam sonar system for performance evaluation.
Main Results:
- Achieved high bearing resolution and suppressed side lobes in sonar data.
- Reduced computational complexity compared to the original R⁻L algorithm.
- Demonstrated improved accuracy in topographic surveys by mitigating the tunnel effect.
Conclusions:
- The proposed fast deconvolved beamforming algorithm enables real-time, high-resolution sonar imaging.
- The algorithm enhances image clarity, detail, and target discrimination in 2D acoustic modes.
- Validated performance with both simulated and real-world sonar data.
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