Theoretical Advances in Current Estimation and Navigation from a Glider-Based Acoustic Doppler Current Profiler (ADCP)
This work addresses a domain-specific problem for underwater glider navigation and current estimation, representing an incremental improvement by refining existing mathematical methods.
The paper tackled the problem of estimating glider position, velocity, and subsurface currents from ADCP measurements by identifying and correcting an incorrect independence assumption in prior methods, resulting in a joint probability model that extends Kalman smoothing with efficacy confirmed through detailed simulations.
We examine acoustic Doppler current profiler (ADCP) measurements from underwater gliders to determine glider position, glider velocity, and subsurface current. ADCPs, however, do not directly observe the quantities of interest; instead, they measure the relative motion of the vehicle and the water column. We examine the lineage of mathematical innovations that have previously been applied to this problem, discovering an unstated but incorrect assumption of independence. We reframe a recent method to form a joint probability model of current and vehicle navigation, which allows us to correct this assumption and extend the classic Kalman smoothing method. Detailed simulations affirm the efficacy of our approach for computing estimates and their uncertainty. The joint model developed here sets the stage for future work to incorporate constraints, range measurements, and robust statistical modeling.