Award Winners
1st Place, Poster Presentation
Evaluation of CubeSat Beacon Transmitter and CubeSat Telemetry Decoding
By Emma Yee
Westlake High School
Supervisor: Aaron Kerkhoff and David Munton, Space and Geophysics Lab, ARL:UT
Abstract
Cubesats are small satellites designed for low-cost space and atmospheric study. Approximately one liter in volume and weighing no more than one kilogram, these satellites use less than 2W of power. The Beacon Apparatus Satellite for Ionospheric Content Surveillance (BASICS) is a proposed mission to measure the ionospheric total electron content. A dual-frequency transmitter for this Cubesat was purchased, and its performance and capabilities were carefully assessed through a series of tests. These included measuring main and spurious frequency outputs, documenting frequency stability using Allan Deviation, studying the effects of exposure to extreme temperatures, and evaluating phase modulation capabilities. Collected measurements were analyzed using various computer programs created in Python. It was found that all four RF outputs met manufacturer's specifications for spurious signals, frequency stability, and frequency accuracy. Changes in voltage input proved successful in modulating signal phase angles and it was shown that the transmitter could produce a phase modulated wave consisting of a carrier mixed with a modulating wave encoded with binary data. From test results, the dual-frequency transmitter was deemed suitable for use on BASICS, although the transmitter's frequency instability over varying temperatures was higher than desired. Methods for extracting the information-carrying phase modulation were devised using low-pass filtering via Discrete Fourier Transform and boxcar averaging. By calculating changes in phase angle and decoding the binary information, data could be obtained from the Cubesat.
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2nd Place, Poster Presentation
An Application of the A* Algorithm to Autonomous Submarine Navigation
By Matthew Chang
Westlake High School
Supervisor: Brian LaCour, Signal and Information Sciences Lab, ARL:UT
Abstract
This paper presents the research and development of a simulation of autonomous submarine navigation. The goals of this project were to develop a simulation that accurately models submarine kinematics and tactics. The key innovation lies in the formulation of costs to be used in the A* algorithm, which is a widely used heuristic global path finding algorithm. As an extension of the traditional cost calculation, we added another cost criterion that corresponds to the predicted risk of detection from several known passive sensors. The risk of detection is based on simple acoustic physics and a signal-threshold model with a fixed false-alarm rate. The A* algorithm produces a node based path which is then converted into a set traversable waypoints. The submarine is modeled as a Newtonian free-body experiencing the forces of thrust, drag, and centripetal acceleration. Using basic mechanics, and presuming a piecewise arc trajectory, the necessary submarine maneuvers to follow the generated path can be calculated. Our algorithm, when tested against a probabilistic tracking system being developed in SISL, proved significantly less detectable than the previously available model for submarine motion. Our model for a tactical submarine not only serves as a tool in the development of new tracking techniques, but also has the potential to serve as a platform for the navigation of unmanned submarines in the field.
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3rd Place, Poster
Presentation
Acoustic Tracking
By Ryan Zimmerman
L.C. Anderson High School
Supervisor: Martin Barlett, Signal and Information Sciences Lab, ARL:UT
Abstract
The objective of this project was to create software to localize a deep sea sensor as it descends into the ocean in order to more accurately determine the final location of the sensor. This has become essential as the sensors can drift several kilometers as they descend thousands of meters into the ocean. The task was accomplished through the use of horizontal current profile data, triangular localization and eigenray files. The first part of the project was creating a prediction program in order to obtain test values for later use. This program had to be able to recognize and account for variations in vertical and horizontal velocity. When this method of tracking is in actual use, a modem attached to the sensor will transmit depth data at a specific time, which is used to calculate the amount of time for the sound to reach the receiver. A test set of data, found from an experiment conducted at the Lake Travis Test Station, was used to check the localization method that was developed. This localization included the ability to find the intersection of circles based on the returned range values from eigenray files. This model was run and successfully plotted in Google Earth.
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