Observability Analysis and Navigation Filter Optimization of High-Orbit Satellite Navigation System Based on GNSS

Abstract

Global Navigation Satellite System (GNSS) can be applied for the navigation of the high-orbit satellites. The system observability will change due to the changes in the visible satellite numbers and the spatial geometry between the navigation satellites and the users in the navigation system. The influence of the observability changing is not considered in the traditional navigation filter algorithm. In this paper, an optimized navigation filter method based on observability analysis is proposed. Firstly, a novel criterion for the relative observable degree is proposed for each observation component by making use of observation data from previous and posterior time simultaneously. Secondly, according to the relationship between observability and navigation filter accuracy, a novel optimized navigation filter method is constructed by introducing an adjusting factor based on the relative observable degree. Through the comparative simulations with the traditional Extended Kalman Filter (EKF), the optimized navigation filter method can reduce the estimation error of position and velocity by about 36% and 44% respectively. Therefore, the superiority of the proposed filter optimization algorithm is verified.

GNSS Signal Acquisition Algorithm Based on Two-Stage Compression of Code-Frequency Domain

“…The global navigation satellite system (GNSS) includes constellations of satellites orbiting over the earth's surface that provide continuous positioning, navigation, and timing (PNT) services anywhere in the world or near-earth space, under any weather conditions [1][2][3]. The first stage of a GNSS receiver is the acquisition, which plays a very important role in signal synchronization, whose aim is to detect the signal and roughly estimate the code phase and the Doppler frequency of the satellite in the field of view.…”