隨著科技的進步，微型衛星於航空天文領域愈來愈廣受歡迎，尤其是近年來逐漸成為標的的「立方衛星」已經主宰許多學術研究中的太空科學計劃。由於立方衛星的體積較其他衛星小且製造時程較短，愈來愈多國家與學校單位偏好使用立方衛星來發展衛星任務。於發射端中，為了增加火箭乘載的使用效率，立方衛星安裝於一種特殊製作的發射載具P-POD，這個裝置可以容納多個立方衛星於火箭發射端以增加火箭的乘載效率。由於此裝置的設計，立方衛星群將以「搭載」方式進行發射，在發射後的初期軌道階段中，立方衛星群將以叢集排列的形式運行於特定軌道；此外由於立方衛星的發射頻帶多操作於極高頻頻段與超高頻頻段，此現象將導致地面站的接收人員難以辨認衛星所在的位置。本論文將提出應用都卜勒效應來辨識低地軌道的叢集立方衛星；在實驗的流程中，將使用尚未更新的衛星軌道參數來追蹤並模擬衛星通過地面站所產生的都卜勒效應曲線，其中以軟體定義無線電做為接收器以記錄特定頻寬的叢集衛星訊號，最後將所收集的訊號濾雜訊、時頻分析等後處理並與模擬的訊號加以比對，再利用SGP4軌道模型計算出衛星軌道參數以得到更新的兩線元素，如此便可辨識叢集立方衛星的位置與速度。本論文的貢獻在於運用兩線元素中的軌道參數來追蹤低地軌道的叢集立方衛星信標訊號，透過都卜勒效應辨識叢集衛星的位置與尚未更新的兩線元素，並在不依賴衛星定位系統的情況之下估算衛星通過地面站的位置與速度以提升地面站追蹤衛星的準確度。

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.

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