# Artificial Intelligence-Empowered Doppler Weather Profile for Low-Earth-Orbit Satellites
## 2 Methodology
### LEO Satellite Tracking Radar System  
In the initial task, the study examines a space surveillance radar tracking system that employs a low-fidelity model to forecast the projected orbit of each satellite. The satellite scenario object imports a satellite orbit constellation defined within a Two Line Element (TLE) file, a widely used format for storing satellite orbital information [25]. The TLE file containing orbital data for two satellite constellations, Globalstar and International Space Station NAUKA (ISS NAUKA), has been chosen to examine their detection and tracking capabilities. The imported satellite orbits undergo propagation using the Simplified General Perturbations-4 (SGP4) orbit propagation algorithm [26], which is renowned for its accuracy with objects in low Earth orbit. These orbits are used as a reference point for evaluating the radar's capability of tracking to find the latest satellites. Subsequently, synthetic detection and tracking scenarios are generated through a space surveillance radar simulation. This simulation involves configuring two radar stations with strategically placed fan-shaped radar beams to enhance detection rates by overlapping satellite orbits. Following this, radar detection simulations and trajectory monitoring were carried out for two designated Australian stations, specifically Perth and Brisbane, positioned strategically in an East-West orientation, spanning 24 h commencing on 1 January 2024, as shown in Figure 1. An evaluation of the accessibility between LEO satellites and the Australian ground station was conducted to determine the visibility of the ground station to the satellites. This analysis helps to identify satellites in the line of sight of the ground station at any given moment. Each station is equipped with a radar system tailored to find the LEO satellites, with the following specifications:  
* Is capable of detecting a 10 dBsm object at a range of 2000 km. * Effectively and accurately aligns objects in directions within a 100 m margin of error at a distance of 2000 km. * Provides 30 degrees in elevation and a range of 120 degrees in the azimuth. * Is positioned to observe the sky and monitor space activities. The radar models yielded detections which were used to estimate satellite orbits. A Joint Probabilistic Data Association (JPDA) tracker [27] was chosen for its efficient tracking capabilities and optimal use of computational resources. A tracking filter was established for the tracker, employing a simplified model, like Keplerian integration, rather than SGP4, to track satellite movements. Any inaccuracies in the target's motion model were addressed through measurement updates and the integration of process noise within the filter. Subsequently, radar detections were simulated to track satellites, ensuring accurate tracking of each satellite's position. We generated a comprehensive record of the constellation's states over 12 h, followed by a simulation of radar detections and track generation. After five hours of diligent tracking efforts, approximately half of the constellation was successfully tracked. It presents a significant challenge to uphold pathways with incomplete orbit coverage, as satellites can remain unnoticed for an extended duration in this arrangement. It is anticipated that if we add further stations for tracking, it will enhance the overall detection ability. The assignment metrics, which evaluate tracking performance by comparing objects, are outlined in Figure 2. We used orbit data from Two Line Element (TLE) files to calculate and visually represent satellite trajectories within our simulation software tool. The study uses the unscented Kalman filter [28] with a Keplerian motion model, setting Alpha to 1, Beta to 0, and Kappa to 0 to ensure robustness for longer forecasting periods. Latency has been attributed to the considerable distance between satellites and the Earth. Furthermore, LEO satellites have been observed to reduce latency as opposed to