An Improved Inverse Beamforming Method: Azimuth Resolution Analysis for Weak Target Detection

Area of Science:

• Signal Processing
• Acoustics
• Array Signal Processing

Background:

• Inverse Beamforming (IBF) is a standard technique for enhancing azimuth resolution in sonar systems.
• However, IBF struggles with weak targets due to enhanced side lobes, limiting its applicability.
• Improved azimuth resolution and weak target detection remain critical challenges in passive sonar.

Purpose of the Study:

• To propose an improved inverse beamforming algorithm (GIBF) that enhances azimuth resolution while maintaining weak target detection capabilities.
• To analyze the underlying causes of side lobe generation in IBF.
• To validate the performance of GIBF using simulations and real-world passive sonar data.

Main Methods:

• Analysis of phase compensation to understand IBF side lobe generation.
• Development of the GIBF algorithm by replacing Toeplitz averaging with phase construction.
• Theoretical derivation and validation through simulations across various signal-to-noise ratios.
• Application and testing on passive sonar data.

Main Results:

• GIBF improves azimuth resolution from N sensors to the standard of 2N-1 sensors.
• The GIBF algorithm demonstrates superior performance in detecting weak targets compared to standard IBF.
• Analysis of passive sonar data shows clearer trajectories on azimuth history diagrams and robust weak target detection.
• GIBF integration with conventional beamforming and minimum variance distortionless response (MVD) algorithms confirms its broad applicability.

Conclusions:

• GIBF effectively enhances azimuth resolution and weak target detection in passive sonar systems.
• The proposed phase construction method in GIBF mitigates side lobe issues inherent in traditional IBF.
• GIBF offers a robust and applicable solution for advanced direction of arrival estimation in challenging acoustic environments.