||Tracking and Identifying a Cluster of CubeSats Using Doppler Shift Effect
||Department of Electrical Engineering
A Cluster of CubeSats
Doppler Shift Effect
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.
List of Tables VIII
List of Figures IX
Chapter 1 Introduction 1
1.1 Background and Literature Review 1
1.2 Motivation and Challenges 8
1.3 Thesis Organization 10
Chapter 2 Satellite Tracking System 11
2.1 Satellite Signals 11
2.1.1 Beacon Signal Transmission 11
2.1.2 Doppler Shift Effect 13
2.2 Ground Station System 16
2.2.1 Tracking System at NCKU 17
2.2.2 Software Defined Radio (SDR) 20
2.2.3 Two-Line Element (TLE) 22
2.2.4 SGP4 Model 26
Chapter 3 Processing Algorithm 30
3.1 Algorithm Overview 30
3.2 Experiment Procedure 32
Chapter 4 Result and Analysis 49
4.1 Experiment on 2014/01/21 50
4.2 Experiment on 2014/01/22 61
4.3 Experiment on 2014/02/10 72
4.4 Results and Discussions 83
Chapter 5 Conclusion and Future Work 85
5.1 Conclusion 85
5.2 Future Work 86
Appendix A 92
Appendix B 94
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