Enhancing Space Situational Awareness through Multi-Station Optical Tracking of LEO Satellites Using the Taiwan Meteor Detection System

Project Description

In the age of “New Space,” the number of low-Earth orbiting (LEO) satellites is increasing exponentially due to the rapid deployment of large-scale commercial constellations. As orbital congestion intensifies, the need for robust Space Situational Awareness (SSA) becomes ever more critical. SSA provides the foundational capability to detect, track, catalog, and predict the motion of space objects, thereby ensuring the long-term sustainability of the near-Earth space environment. Accurate monitoring of LEO satellites is essential not only for collision avoidance and mission safety, but also for maintaining reliable communication, navigation, and Earth observation services.

It is therefore imperative to continuously monitor the orbital evolution of LEO satellites with high temporal resolution and geometric diversity. One effective approach is to employ all-sky wide-angle optical cameras to provide continuous sky coverage and complementary tracking capability to radar-based systems. The Taiwan Meteor Detection System (TMDS), managed by the NCU Institute of Astronomy, offers such an opportunity. Originally designed for meteor observations, TMDS can be adapted to track artificial satellites and contribute to a regional SSA network.

Because TMDS consists of multiple observation stations distributed across Taiwan—including Lulin Observatory, Kenting, and Kinmen—the integration of multi-station datasets enables improved orbital element determination through geometric triangulation and cross-validation. The distributed configuration enhances angular measurement accuracy, reduces systematic biases, and strengthens orbit reconstruction reliability.

The primary objective of this project is to develop and validate, using simulated datasets, a software and algorithmic framework for optical orbit determination of LEO satellites. The project involves building a complete processing pipeline, including image calibration, satellite trail extraction, astrometric reduction, and short arc, angle only orbit estimation. To quantitatively assess estimation errors and algorithm suitability, we will conduct controlled simulations and Monte Carlo experiments to compare multiple estimation approaches. The performance of these algorithms will be evaluated in terms of accuracy, numerical stability, convergence behavior, and uncertainty consistency. Through this project, participating students will gain hands-on experience in orbital dynamics, nonlinear estimation methods, optical image processing, and quantitative error analysis. The validated framework developed in this project will serve as a foundation for future integration with observational data from Lulin Observatory and other TMDS stations, contributing to Taiwan’s long term space situational awareness capability.