Nexteq’s Integer Ambiguity-Resolved Precise Point Positioning System

摘要

To obtain high accuracy results using the globalpositioning system (GPS), real-time kinematic (RTK) andprecise point positioning (PPP) technologies arecommonly used. Traditional RTK technologies arelimited to baseline lengths of less than 50 km and do nottake full advantage of the information contained in anetwork of reference receivers. On the other hand, whilethe accuracy of PPP has been widely demonstrated, thefull adoption of this technique has been limited by its longconvergence time.With the development of new PPP technologies, Nexteqhas been targeting high accuracy GNSS users who havetraditionally relied on RTK or differential GPS solutions.Currently, Nexteq offers Freedom and i-PPP positioningsolutions which enable global sub-meter to sub-foot realtimeaccuracy for consumer and professional grade singlefrequency chipsets with virtually no initialization time.These technologies have been able to reduce the cost andlogistics required for survey grade geographic informationsystems (GIS) operations which in the past typicallyrequired a base station and/or post-processing to achieve acomparable level of accuracy.For users requiring high accuracy, Nexteq offers dualfrequency PPP technology which can achieve 10 cmhorizontal RMS in real-time. However, as with all highaccuracy PPP systems, typical convergence times varyfrom tens of minutes, up to an hour depending on localconditions (such as multipath and atmospheric effects).In the past few years, researchers have been able toimprove both the convergence and accuracy of the PPPtechnique by resolving the integer nature of the carrierphase ambiguities. In order to achieve this, the fractionalbiases which exist on the carrier phase and pseudorangeobservations must be explicitly modeled using a networkof continuously operating receivers.In this contribution, we describe the development of aPPP system which enables ambiguity resolution at aremote receiver. This includes a description of the systemarchitecture, as well as the technology supporting thestate-space corrections, determination of the fractionalbiases and end user algorithm.Using these corrections, the improvement in accuracy andconvergence of the ambiguity-resolved PPP solutionswith respect to traditional float PPP solutions are shown.Additionally, the impact of the network size on the qualityof the fractional biases will also be discussed.