Energy efficient signaling strategies for tracking mobile underwater vehicles

Abstract

Positioning is a crucial requirement for mobile underwater systems. Since GPS is not available underwater the position of vehicles has to be estimated over time. Underwater navigation techniques often rely on acoustic communication with reference beacons that know their location. These beacons in effect act as GPS satellites for underwater vehicles. The beacons may be buoys or vehicles on the surface with access to GPS or they may be deployed on the sea floor at known locations. Since both the beacons and underwater vehicles are battery operated, energy is a key constraint. This is further aggravated by the fact that the energy required to acoustically communicate underwater is high even over moderate distances. Since the acoustic signaling required for tracking vehicles is a recurring cost, we propose to minimize the energy consumption by optimizing the extent of signaling used for localization. Localization techniques that exclusively rely on estimates of time of flight (or time difference of arrivals) require transmissions from beacons to be nearly concurrent. This allows position to be estimated at each point in time based on geometric constraints alone, neglecting vehicle motion between transmissions. Alternatively if vehicles have some knowledge about their motion either from models or from direct measurements of their acceleration and heading as obtained from an on-board inertial measurement unit (IMU), other techniques can take this information into account. The extended Kalman filter, particle filters or factor-graph based Maximum Likelihood (ML) trajectory estimation methods effectively combine IMU measurements with geometric constraints obtained from acoustic time of flight measurements. One of the advantages of such an approach is that beacon transmissions no longer have to be concurrent. In this paper we use the Maximum Likelihood (factor-graph based) tracking method to find the best schedule for beacon transmissions for a fixed signaling rate (or average power consumption). We explore a number of possible transmission schemes and evaluate their performance as a function of relevant system parameters, specifically, the type of motion measurements available, the accuracy of these measurements and the number of beacons. We also evaluate our proposed schemes on experimental data obtained from sea trials that were conducted off the coast of San Diego. Our experimental and simulation results show that even if coarse information is available about the vehicle's motion, the localization performance can be improved for a fixed signaling rate by appropriately lagging transmissions from reference beacons.