Motion Estimation From Doppler and Spatial Data in SONAR Images

Abstract

Motion estimation is critical for the localization of autonomous underwater vehicles. Current SONAR-based techniques exclusively utilize either Doppler or spatial measurements. However, these measurement domains are complementary to each other; Doppler measurements directly measure radial motion, whereas spatial measurements uniquely observe angular motion. Therefore, this article presents SONARODO (SONAR Odometry), a novel real-time motion estimation algorithm for 2-D forward-looking SONARs. It depends on a largely decoupled motion estimation process that better utilizes each measurement domain for their respective strengths. Specifically, it estimates translational motion from Doppler-azimuth images and rotational motion from range-azimuth images. While this method does require a SONAR that can provide both image types, it was designed to ensure robustness to featureless seafloor environments and low-resolution images. This article's validation with high-fidelity simulation data demonstrated that SONARODO offers accuracy and computational cost advantages over related motion estimation techniques.