Inter-Satellite Range Estimation Using Discovery & Resolution Modes for Space Traffic Management

2019 
The increase in satellite launches has led to a jump in the number of satellites orbiting Earth to over 1900 active satellites to date. Most of these satellites rely on the two-line elements (TLEs) to define the satellite tracks. However, the accuracy obtained from TLEs is insufficient for accurate satellite collision predictions which led to the undeniable uncertainty regarding satellite conjunction assessment. This paper extends the research conducted about investigating the implementation of a new inter-satellite ranging instrument by proposing two operational modes namely Discovery and Resolution. Discovery allows long-distance satellite detection and fast range estimation from the received signal strength indicator (RSSI). This ensures a larger observation time-window for the Resolution mode to define precisely the nature of the satellite encounter. The system switches to Resolution when the relative range between the satellites source and observer decreases below 10 km according to the scenario studied. Unlike Discovery, Resolution estimates the range from the round-trip propagation delay using sequential ranging techniques. Results reveal that RSSI range measurements are prone to heavy fluctuations due to the path loss variations. In fact, a standard deviation of 63 km for the ranging errors over 1s measurement time is measured however, these measurements are obtained within 2-µs time intervals. On the other hand, Resolution measures the range in chips by calculating the argument of the maxima of the cross-correlation function (CCF) output between the transmitted and the received sequences. Results using Resolution show that an accuracy of 110-m is obtained from a ranging sequence of 800 kcps during 1 s observation window. This value is drastically improved compared to the results achieved with Discovery but with the cost of an acquisition-and processing-time of 20 ms compared to 2 µs attained with Discovery.
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