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An efficient sparse method for direction-of-arrival estimation in the presence of strong interference
Chenmu Li1, Guolong Liang1, Longhao Qiu1
1College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin, 150001, China.
The Journal of the Acoustical Society of America
|March 1, 2023
Summary
This study introduces an efficient sparse method to improve target direction-of-arrival (DOA) estimation, significantly reducing interference effects. The novel approach enhances accuracy and efficiency, even with closely spaced signals.
Area of Science:
- Signal Processing
- Array Signal Processing
- Electromagnetics
Background:
- Direction-of-arrival (DOA) estimation is crucial for various applications.
- Strong interference signals can degrade target DOA estimation accuracy, especially when DOAs are close.
- Existing methods struggle to effectively mitigate the impact of strong interference on weak target signals.
Purpose of the Study:
- To propose an efficient sparse method for robust DOA estimation in the presence of strong interference.
- To reduce the masking effect of strong interference on weak target signals.
- To improve the accuracy and efficiency of DOA estimation algorithms.
Main Methods:
- Development of an efficient sparse method for DOA estimation.
- Application of an on-grid grid evolution technique for nonuniform grid refinement.
- Minimization of computational complexity while maintaining estimation accuracy.
Main Results:
- The proposed sparse method significantly reduces the impact of strong interference on target DOA estimation.
- The on-grid grid evolution technique enhances computational efficiency.
- Numerical simulations and experimental results validate the method's superior performance.
Conclusions:
- The proposed method offers higher efficiency and better DOA estimation performance compared to state-of-the-art techniques.
- This approach effectively addresses the challenges posed by strong interference in DOA estimation.
- The technique provides a robust solution for accurate DOA estimation in complex signal environments.
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