Satellite Tracking

Purdue Space Program - Astrodynamics & Space Applications [PSP ASA]

A glimpse into satellite orbit analysis.

Since December 2024, our student-led undergraduate research initiative has centered on investigating the orbital perturbations induced by solar radiation pressure (SRP) and Earth's magnetic field affecting satellite trajectories in low-Earth orbit (LEO). We are preparing to showcase our findings at the forthcoming Spring Research EXPO hosted by Purdue University.

Project Background

The influence of solar radiation pressure (SRP) and the Sun’s activity cycles can disrupt satellite orbits, resulting in inaccuracies in predicting their positions. This poses challenges in trajectory forecasting, collision avoidance, and overall orbital management. As outlined earlier, the satellite tracking project under PSP ASA aims to compare theoretical predictions with observed behaviors of various CubeSats to enhance the accuracy of solar-induced perturbation modeling.

Online satellite catalogs provide up-to-date measured state data for numerous satellites in the form of two-line element (TLE) datasets. This data is first converted into state vectors, which are then used to propagate the satellite’s orbit while accounting for all known orbital perturbation sources except for SRP. These calculated orbital parameters serve as a control model for later comparison.

Simultaneously, the same initial state data is processed through a second model designed to empirically estimate the orbital perturbations caused by SRP. Both models generate predictions for the satellite’s future states. After approximately two days, newly observed satellite data is collected and directly compared against both models. This comparison quantifies the impact of SRP on satellite trajectories and evaluates the accuracy of the SRP model. The insights gained from this analysis are used to refine the SRP model, improving its ability to predict future satellite states based on observed data.

My Work

Apart from the project manager, I was the first member to join this research team. In this role, I was responsible for conducting an extensive literature review and drafting the research abstract for the project's proposal to the research fair. Additionally, I developed a comprehensive step-by-step framework outlining the process for acquiring TLE data, determining satellite states, propagating orbits, and comparing predicted future states with observed data.

To validate this methodology, I analyzed the orbit of VZLUSAT-2, a 3U Czech CubeSat with publicly available state data from open-source satellite catalogs. Using this data, I collaborated with the Chief Astrodynamicist of PSP ASA to develop an extensive computational model for orbit propagation. The control model generated by this code, displayed on the top left, served as a baseline for comparison. By analyzing the CubeSat’s predicted state two days after the initial data acquisition, I quantified the discrepancies between the calculated and observed orbits. This documented research process now serves as a guideline for other team members conducting individual satellite orbital analyses.

In addition to orbit propagation, the developed code also determines the eclipse windows the satellite experiences throughout its orbit. The resulting eclipse data, illustrated in the lower left chart, can be cross-referenced with observed satellite temperature fluctuations and solar cell charging periods. This provides an additional validation layer for comparing the calculated and observed orbital behavior of the CubeSat.

Skills Learned & Applied

Technical Skills

MATLAB
Technical Writing (Overleaf)
Data Analysis (Microsoft Excel & MATLAB)
Ansys STK
Python
Orbital Mechanics

Personal Skills

Leadership
Teamwork
Communication

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