The Satellite Orbit Control And Orbit Determination Algorithms

With the diversification and complication of space mission requirements, it is necessary for orbital control and orbital determination to meet these requirements. However classical methods could not meet these requirements in some cases. This paper improved these methods based on the requirements 0There are two methods for conventional orbital control: one is algebra method which deals with the problems by optimization based on orbit geometry characteristics The first method is applied when we adopt impulsive control, but in the multiobjective cases the method has its limitation. The other method is Pontryagin maximum value principle dealing with low thrust control problem. However when the system is very complex, especially when the system contains uncertain factors, the method is not effective. In this paper we introduce some intelligent control methods to solve them.Firstly the paper introduces evolutionary algorithms(EA), presents the improved SPEA, which adopts multiple-chromosome crossover and Cauchy mutation instead of bi-chromosome crossover and norm mutation, also gives convergence analysis of SPEA. Then the paper applies EA and SPEA to an orbital transformation problem.- time-energy optimization o The paper also solve low thrust control problem of relative motion using fuzzy logic.The classical algorithms for orbital determination are least square estimation (LSE) and Kalman filtering. But when the observing data contains nonlinear factors, which is always encountered in practice, the performance of the algorithms is very poor. In this paper semiparametric regression is presented to solve the problem, moreover the algorithm is given. It is an iterative process between linear estimation and nonlinear estimation. The linear estimation is LS estimation and the nonlinear estimation is a wavelet denoising process of residual. In contrast to conventional LSE and Kalman filtering, the algorithm has higher performance in precision orbit determination. Moreover the algorithm is tested by simulation data and real observed data, and the computing results show that the algorithm is very effective.