Direct position determination of multi-tone acoustic signals using off-grid sparse Bayesian learning in the
Wei Wang1,2, Shefeng Yan1,2, Jirui Yang1,2
1Institute of Acoustics, Chinese Academy of Sciences, Beijing, 100190, China.
The Journal of the Acoustical Society of America
|April 17, 2025
Summary
This study introduces an advanced algorithm for precise underwater target localization using multi-tone acoustic signals. The new method significantly improves positioning accuracy and target resolution compared to existing techniques.
Area of Science:
- Acoustics
- Signal Processing
- Underwater Surveillance
Background:
- High-precision target localization is essential for underwater surveillance.
- Existing direct position determination (DPD) algorithms face limitations in accuracy due to fixed grids and pseudo-target interference.
Purpose of the Study:
- To propose an improved DPD algorithm for multi-tone acoustic signals.
- To enhance positioning accuracy and multi-target resolution in underwater environments.
Main Methods:
- Developed an off-grid sparse Bayesian learning-based DPD algorithm (DPD-offGSBL).
- Established a unified frequency-domain data model for coherent, incoherent, and mixed signals.
- Formulated an off-grid sparse signal representation and explored joint sparsity among arrays.
Main Results:
- DPD-offGSBL demonstrates superior positioning accuracy and multi-target resolution.
- The algorithm approaches the Cramér-Rao bound (CRB) under various conditions.
- Validated practical applicability using the SWellEx-96 Experiment Event S5 for single underwater acoustic source localization.
Conclusions:
- The proposed DPD-offGSBL algorithm offers a significant advancement in underwater acoustic localization.
- It effectively addresses limitations of traditional methods, providing higher precision and better resolution.
- The algorithm is robust and applicable to real-world underwater surveillance scenarios.
