一种利用稀疏贝叶斯学习的抗伪峰频差方位估计方法
The azimuth estimation method against spurious peak frequency difference through sparse Bayesian learning solves the problem of grating lobe and spurious peak interference in sparse arrays, and achieves more accurate azimuth estimation and target detection, which is applicable to underwater acoustic array signal processing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- INST OF ACOUSTICS CHINESE ACAD OF SCI
- Filing Date
- 2026-01-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies in sparse arrays suffer from problems such as increased grating lobes, increased beamwidth, noise effects, and spurious peak interference in multi-target scenarios. In particular, when the sound velocity profile and array configuration are mismatched in marine environments, the azimuth estimation performance deteriorates.
A spurious peak frequency difference azimuth estimation method is adopted using sparse Bayesian learning. By constructing a dictionary matrix and using sparse Bayesian learning to reconstruct the frequency difference sparse signal, the signal strength stability is quantified, spurious signal strength is iteratively removed, and the joint spectrum matrix is optimized to obtain accurate azimuth estimation results.
It effectively removes spurious peaks, improves the accuracy and robustness of orientation estimation, enhances the ability to distinguish nearby targets, reduces the impact of noise, and improves the target detection capability in complex marine environments.
Smart Images
Figure CN122017727B_ABST