First Results from Virtual Reference Station (VRS) and Precise Point Positioning (PPP) GPS Research at the Western Australian Centre for Geodesy

Over the past 18 months, a team in the Western Australian Centre for Geodesy at Curtin University of Technology, Perth, has been researching the optimum configurations to achieve long-range and precise GPS-based aircraft positioning for subsequent airborne mapping projects. Three parallel strategies have been adopted to solve this problem: virtual reference stations (VRS), precise point positioning (PPP), and multiple reference stations (MRS). This paper briefly summarises the concepts behind the PPP and VRS techniques, describes the development and testing of in-house software, and presents the latest experimental results of our research. Current comparisons of the PPP and VRS techniques with an independently well-controlled aircraft trajectory and ground-based stations in Norway show that each deliver precisions of around 3 cm. However, the implementation of more sophisticated error modelling strategies in the MRS approach is expected to better deliver our project’s objectives

An Approach for Instantaneous Ambiguity Resolution for Medium- to Long-range Multiple Reference Station Networks

Integer ambiguity resolution (AR) is a prerequisite for all high-precision (centimetre level) GPS applications that utilise multiple reference station (MRS) networks. However, due to the presence of distance-dependent GPS errors, notably atmospheric refraction, AR across the network is difficult on an epoch-by-epoch basis, especially for medium- to long-range (typically 30?130 km as used here) MRS networks. This paper presents an approach for medium- to long-range instantaneous AR for MRS networks, based on an ionosphere-weighted observation model and network geometry constraints, along with a multiple ambiguity validation test procedure. The performance of the proposed method was demonstrated through two case-study examples from Australia and Norway. Our test results show that the instantaneous AR success rate varied from 93% (131 km baseline) to 98% (35 km baseline).It is also shown that the adopted high-precision prediction models for the double-difference (DD) ionospheric delay and residual tropospheric zenith delay (RTZD) are of benefit to the high success rate of the network AR. Due to its epoch-by-epoch nature, the proposed approach is insensitive to cycle-slips, rising or setting satellites, or loss-of-lock