Stabilized Adaptive Steering for 3D Sonar Microphone Arrays with IMU Sensor Fusion

TL;DR

This paper introduces a real-time, IMU-assisted adaptive beamforming method for 3D sonar arrays that improves image stability on uneven terrain, reducing artifacts and enhancing temporal consistency.

Contribution

It presents a novel software-based adaptive steering technique combining IMU data with beamforming, improving in-air 3D sonar imaging stability without mechanical stabilization.

Findings

Significant improvement in acoustic image stability and consistency.

Real-time GPU-accelerated implementation with 210ms average execution time.

Effective compensation for transducer directivity energy loss.

Abstract

This paper presents a novel software-based approach to stabilizing the acoustic images for in-air 3D sonars. Due to uneven terrain, traditional static beamforming techniques can be misaligned, causing inaccurate measurements and imaging artifacts. Furthermore, mechanical stabilization can be more costly and prone to failure. We propose using an adaptive conventional beamforming approach by fusing it with real-time IMU data to adjust the sonar array's steering matrix dynamically based on the elevation tilt angle caused by the uneven ground. Additionally, we propose gaining compensation to offset emission energy loss due to the transducer's directivity pattern and validate our approach through various experiments, which show significant improvements in temporal consistency in the acoustic images. We implemented a GPU-accelerated software system that operates in real-time with an average execution time of 210ms, meeting autonomous navigation requirements.