Improving Orbit Prediction of the Two-Line Element with Orbit Determination Using a Hybrid Algorithm of the Simplex Method and Genetic Algorithm

Abstract

With the rapidly increasing number of satellites and orbital debris, collision avoidance and reentry prediction are very important for space situational awareness. A precise orbital prediction through orbit determination is crucial to enhance the space safety. The two-line element (TLE) data sets are publicly available to users worldwide. However, the data sets have uneven qualities and biases, resulting in exponential growth of orbital prediction errors in the along-track direction. A hybrid algorithm of the simplex method and genetic algorithm is proposed to improve orbit determination accuracy using TLEs. The parameters of the algorithm are tuned to achieve the best performance of orbital prediction. Six satellites with consolidated prediction format (CPF) ephemeris and four satellites with precise orbit ephemerides (PODs) are chosen to test the performance of the algorithm. Compared with the results of the least-squares method and simplex method based on Monte Carlo simulation, the new algorithm demonstrated its superiorities in orbital prediction. The algorithm exhibits an accuracy improvement as high as 40.25% for 10 days of orbital prediction compared to that using the single last two-line element. In addition, six satellites are used to evaluate the time efficiency, and the experiments prove that the hybrid algorithm is robust and has computational efficiency.