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Underwater unmanned self track algorithm and platform using the ordinary least squares: a thesis in Electrical Engineering
Thesis   Open access

Underwater unmanned self track algorithm and platform using the ordinary least squares: a thesis in Electrical Engineering

William Edward Sullivan
Master of Science (MS), University of Massachusetts Dartmouth
2023
DOI:
https://doi.org/10.62791/20326

Abstract

A tracking algorithm is developed for passively tracking an underwater vehicle without needing to transmit from an asset or platform. The algorithm requires data collected from an Inertial Measurement Unit (IMU) and detections of acoustic pulses from bottom-mounted projectors. Software is developed to collect and fuse the vehicle’s IMU data with the acoustic detections data. In-water acoustic data is collected and analyzed. A least squares method is developed for synchronous self-track by converting all of the data to possible slant ranges and estimating the most likely track of the asset. The sum of squared errors is minimized for the error between slant ranges based on acoustic measurements and those of the track positions. A modified Newton-Raphson type method is used in a nested form because the regressors are all mutually dependent. The method is modified, in that the derivative of the error function is estimated by evaluating the function at three points. A tracking pinger is integrated with an IMU with acoustic receiver for feasibility.
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