GPS + BDS Network Real-Time Differential Positioning Using a Position Domain Estimation Method

The network real-time differential positioning technique is a good choice for meter and sub-meter level’s navigation. More attention has been paid to the Global Positioning System (GPS) and GPS + GLONASS (GLObal NAvigation Satellite System) network real-time differential positioning, but less on the GPS + BDS (BeiDou Navigation Satellite System) combination. This paper focuses on the GPS + BDS network real-time differential positioning. Since the noise of pseudorange observation is large, carrier-phase-smoothed pseudorange is usually used in the network real-time differential positioning to improve the positioning accuracy, while it will be interrupted once the satellite signal is lost or a cycle slip occurs. An improved algorithm in the position domain based on position variation information is proposed. The improved method is immune to the smoothing window and only depends on the number of available satellites. The performance of the network real-time differential positioning using the improved method is evaluated. The performance of GPS + BDS combination is compared with GPS-only solution as well. The results show that the positioning accuracy can be increased by around 10%–40% using the improved method compared with the traditional one. The improved method is less affected by the satellite constellation. The positioning accuracy of GPS + BDS solution is better than that of GPS-only solution, and can reach up to 0.217 m, 0.159 m and 0.330 m in the north, east and up components for the static user station, and 0.122 m, 0.133 m and 0.432 m for the dynamic user station. The positioning accuracy variation does not only depend on whether the user is inside or outside the network, but also on the position relation between the user and network.

Analysis of Creating Correction Algorithms for GPS Network RTK System

In order to analyze the effect of using different creating correction algorithms and geometry of reference stations on the correction accuracy of a user station, interpolation coefficients (correction quality factors) were calculated based on six algorithms, three experiment networks and two users in different positions. These algorithms include Partial Derivative Algorithm (PDA), Distance-based Linear Interpolation Method (DLIM), Linear Interpolation Method (LIM), Low-order Surface Model (LSM), Linear Combination Model (LCM) and Least - Squares Collocation (LSC). By comparative analysis on these factors a conclusion can be drawn as follow, LIM and LCM algorithms are better than others in creating correction; the geometry of reference stations involved in calculation needs to be carefully considered.