Unscented Batch Sequential Filter and Its Application to Relative Orbit Determination for Formation Flight

Abstract

AbstractThis paper derives a new batch sequential estimator utilizing “Unscented Transformation.” It is a natural extension of the Unscented Batch Filter(UBF), and it inherits advantages of the UBF, such as being able to deal with nonlinear system equations directly, and providing a higher convergence capability starting from poorer initial guesses compared with conventional Bayesian filters. This paper applies the proposed filter to a relative orbit determination for a multiple spacecraft formation flight mission using relative range measurement information. A major challenge of this problem is that, since the available initial guess of estimation and the dynamic range of the relative orbital motion itself are of the same order, relatively higher convergence capability is required for the estimator to realize an accurate guess. The Bayesian filter, which is generally applied to this kind problem, is found to have an insufficient convergence performance. Numerical simulations show that the proposed “Unscented Batch Sequential Filter” provides a better convergence performance without taking longer computational time than other conventional filters.