A Two-Stage Optimization Model for Satellite Tracking with Noncooperative Ground-Based Equipment in NGSO Constellations

With the explosive growth in the number of NSGO satellites, there is an increased demand for satellite tracking technology, making the accurate prediction of satellite trajectory and optimization of target tracking efficiency crucial. This paper proposes a strategy for tracking NGSO satellites, which employs a two-stage stochastic model with a greedy approach to optimize the real-time prediction of multiple NGSO satellite passes and improve the efficiency of noncooperative ground equipment. The first stage of the model employs SGP4/SDP4 functions for initial orbit predictions, isolating satellite data from ground equipment performance. The second stage iteratively refines these predictions, addressing the complexities associated with noncooperative ground equipment, constrained resources, the high frequency of NGSO constellation satellites pass, and effective target management. The resulting two-stage model achieves precise and efficient operations, effectively overcoming the traditional challenges of stochastic optimization in dynamic conditions involving multiple satellites. It successfully copes with the exponential surge in computational requirements as the number of satellites increases. A case study with an antenna system validates the practicality and effectiveness of the model. The optimized sequence significantly enhances overall performance concerning efficiency, utilization, idle time, angular displacement, and trajectory symmetry, achieving a 27.48% improvement over the traditional solution and a notable 58.33% increase in the number of effectively tracked satellites, all within a rapid 15-second execution window.