Spacecraft INS/CNS/Pulsar integrated Positioning Navigation and Timing

Abstract

In this paper, robust algorithms of information fusion between Pulsars timing, ranging and positioning with orbital dynamical model of explorer spacecraft is demonstrated with combination to inertial navigation system. Pulsar/CNS integration is considered in this work and was recently investigated using multiple variant of nonlinear filtering approaches, providing an interesting advances and results. However, due to the colored measurement noise from pulsars time of arrival measure, robust nonlinear filter has been derived based on Gauss Quadrature Kalman filters at different degrees. Moreover, because it has been demonstrated that in the during short period of observation, and minimum photons numbers, the noise affecting the X-Ray signal becomes not a Gaussian distribution. An alternative solution to this problem is proposed using multiple quadrature Kalman filters derived in the Gaussian Sum framework. At last, as an experimental validation, the Crab pulsar data were used to demonstrate the efficiency of the novel robust filtering approach against non linearity and also colored non Gaussian measurement noises.