Attitude Estimation of AUVs Based on a Network of Pressure Sensors

Alon Baruch, Yair Mazal, Boris Braginsky, Hugo Guterman

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Underwater navigation is a challenging task for Autonomous Underwater Vehicles (AUVs), which requires to estimate the position and orientation of the vehicle. Accelerometer-based attitude estimation is problematic as its accuracy can degrade by up to two orders of magnitude when the AUV is accelerating. Pressure sensors, which are unaffected by acceleration, offer an efficient alternative for determining orientation. This paper offers a method for pitch-and-roll estimation using a network of pressure sensors and a thorough analysis of the method's accuracy including analytical evaluation and the Cramér-Rao lower bound. Then, the method is tested in a simulation. We also provide a way to estimate system performance based on the vehicle's size and the number and accuracy of the sensors.

Original languageEnglish
Article number9044438
Pages (from-to)7988-7996
Number of pages9
JournalIEEE Sensors Journal
Volume20
Issue number14
DOIs
StatePublished - 15 Jul 2020

Keywords

  • Attitude and Heading Reference System (AHRS)
  • Autonomous underwater vehicle (AUV)
  • error analysis
  • marine navigation
  • pressure sensors

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Attitude Estimation of AUVs Based on a Network of Pressure Sensors'. Together they form a unique fingerprint.

Cite this