Motion Estimation from Doppler and Spatial Data in SONAR Images

Chris D. Monaco, Shawn F. Johnson, Daniel C. Brown, Sean N. Brennan

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Article number9118882
Pages (from-to)665-674
Number of pages10
JournalIEEE Journal of Oceanic Engineering
Issue number2
StatePublished - Apr 2021

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Mechanical Engineering
  • Electrical and Electronic Engineering


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