ROBUST NONLINEAR FILTERING OF NAVIGATION SATELLITE MEASUREMENTS

Abstract

A novel approach to processing satellite navigation measurements with high-precision positioning of mobile objects is considered. For its implementation, at the first stage, stochastic nonlinear differential equations of spatial coordinates of a mobile object were obtained from Doppler satellite measurements and their observer's equations were obtained from pseudo-range measurements. The form of the obtained equations allows one to use the methods of the theory of nonlinear and, in particular, robust filtering to estimate the coordinate vector of an object. As a rule, the nature of the type of interference distributions of Doppler and code measurements is uncertain. Therefore, a dynamic robust algorithm was developed to estimate the spatial coordinates of an object. This algorithm is optimal in terms of the minimum criterion of a nonlinear positive determined function from measurement inconsistency determined by the class of interference distributions of Doppler measurements and pseudo-range measurements. The comparative effectiveness of this algorithm with the conventional approach is illustrated by a numerical example.