Tracking and Identifying a Cluster of CubeSats Using Doppler Shift Effect

碩士 === 國立成功大學 === 電機工程學系 === 103 === Along with the advancement of technology, especially in aviation and astronomy, Pico-satellites have become more popular. “CubeSats”, a satellite with a 1 liter volume, have been employed in an increasing number of space science projects for academic research. Ow...

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Bibliographic Details
Main Authors: Chiung-HuiTsai, 蔡瓊慧
Other Authors: Jyh-Ching Juang
Format: Others
Language:en_US
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/88521127911821797049
Description
Summary:碩士 === 國立成功大學 === 電機工程學系 === 103 === Along with the advancement of technology, especially in aviation and astronomy, Pico-satellites have become more popular. “CubeSats”, a satellite with a 1 liter volume, have been employed in an increasing number of space science projects for academic research. Owing to CubeSat’s small size and short development time, several countries and universities have begun developing their own CubeSat missions. In order to improve the efficiency of launching satellites, a new type of launch adaptor, named Poly-Satellite Orbital Deployer (P-POD), was created with multiple mounted CubeSats. Due to this type of launch, there is a unique characteristic for CubeSat launch, a piggyback launch, which means multiple CubeSats form a cluster share a similar orbit in the early orbit phase after deployment. The communication mode of CubeSat is mostly beaconing in the VHF and UHF frequency bands. The conditions for the early orbit phase of a clustered CubeSat launch may cause difficulties to the operator or tracker in the ground station to identify and track the CubeSats. In this thesis, an identification procedure based on Doppler shift effect is proposed and verified to classify a cluster of CubeSats for low earth orbit in the early orbit phase. In the experimental procedure, rough Two-Line Elements (TLEs) are used as reference to simulate the passing orbit. A software defined radio with wide-bandwidth is used as a receiver. The recording beacon signals from a cluster of CubeSats are processed by time-frequency analysis and paired to the prediction result. The deviation of the paired samples would then serve as constraints for Particle Swarm Optimization (PSO) to update the TLEs. The contribution of this thesis is to identify satellites by using Two-Line Element without relying on a satellite positioning system. Consequently, a ground station could predict the orbit of CubeSats more accurately and timely.