Working towards adaptive sensing for terrain-aided navigation
Document Type
Conference Proceeding
Date of Original Version
5-1-2019
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.
Publication Title, e.g., Journal
Proceedings - IEEE International Conference on Robotics and Automation
Volume
2019-May
Citation/Publisher Attribution
Zhou, Mingxi, Ralf Bachmayer, and Brad Deyoung. "Working towards adaptive sensing for terrain-aided navigation." Proceedings - IEEE International Conference on Robotics and Automation 2019-May, (2019): 3450-3456. doi: 10.1109/ICRA.2019.8794149.