Working towards Adaptive Sensing for Terrain-aided Navigation
Mingxi Zhou, Ralf Bachmayer, Brad de Young
Abstract
An adaptive sensing method is presented to control the pinging interval of a downward-looking sonar on an Autonomous Underwater Vehicle. The goal is to conserve energy via adjusting the pinging rate automatically without reducing the localization accuracy when using terrain-aided navigation (TAN). In this paper, the TAN is implemented using a particle filter and a bias velocity estimator developed based on a Kalman filter. The adaptation on the sonar pinging interval is determined based on the depth variation of local seafloor topography which is quantified using a modified Teager Kaiser energy operator. As a result, more measurements are collected on high relief regions, and less measurements are obtained on relatively flat and smooth regions. We evaluated the adaptive sensing method in a simulated environment and applied it to a field data set. The results show that the adaptive sensing method produces an improved navigational accuracy compared to the missions with fixed sonar pinging rates. In the offline field missions, the energy consumed by the altimeter is reduced to about 30% in the adaptive sensing missions compared to continuously sensing missions where the altimeter is pinging consistently without switching off.
BibTeX
@inproceedings{icra2019_workingtowardsad,
title = {Working towards Adaptive Sensing for Terrain-aided Navigation},
author = {Mingxi Zhou and Ralf Bachmayer and Brad de Young},
booktitle = {ICRA 2019},
year = {2019}
}