Abstract

The tropospheric delay is one of the major error sources in precise point positioning (PPP), affecting the accuracy and precision of estimated coordinates and convergence time, which raises demand for a reliable tropospheric model, suitable to support PPP. In this study, we investigate the impact of three tropospheric models and mapping functions regarding position accuracy and convergence time. We propose a routine to constrain the tropospheric estimates, which we implemented in the in-house developed real-time PPP software. We take advantage of the high spatial resolution (4 × 4 km2) numerical weather prediction Weather Research and Forecasting (WRF) model and near real-time GNSS data combined by the least-squares collocation estimation to reconstruct the tropospheric delays. We also present mapping functions calculated from the WRF model using the ray-tracing technique. The performance tests are conducted on 14 Polish EUREF Permanent Network (EPN) stations during 3 weeks of different tropospheric conditions: calm, standard and severe. We consider six GNSS data processing variants, including two commonly used variants using a priori ZTD and mapping functions from UNB3m and VMF1-FC models, one with a priori ZTD and mapping functions calculated directly from WRF model and three variants using the aforementioned mapping functions but with ZTD model based on GNSS and WRF data used as a priori troposphere and to constrain tropospheric estimates. The application of a high-resolution GNSS/WRF-based ZTD model and mapping functions results in the best agreement with the official EPN coordinates. In both static and kinematic modes, this approach results in an average reduction of 3D bias by 20 and 10 mm, respectively, but an increase of 3D SDs by 1.5 and 4 mm, respectively. The application of high-resolution tropospheric model also shortens the convergence time, for example, for a 10 cm convergence level, from 67 to 58 min for the horizontal components and from 79 to 63 min for the vertical component.

Highlights

  • Precise point positioning (PPP) is a well-established and commonly used strategy by the Global Navigation Satellite System (GNSS) community, the realtime PPP is still under development

  • We take advantage of the high spatial resolution (4 9 4 km2) numerical weather prediction Weather Research and Forecasting (WRF) model and near real-time GNSS data combined by the least-squares collocation estimation to reconstruct the tropospheric delays

  • We consider six GNSS data processing variants, including two commonly used variants using a priori zenith total delay (ZTD) and mapping functions from UNB3m and VMF1-FC models, one with a priori ZTD and mapping functions calculated directly from WRF model and three variants using the aforementioned mapping functions but with ZTD model based on GNSS and WRF data used as a priori troposphere and to constrain tropospheric estimates

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Summary

Introduction

Precise point positioning (PPP) is a well-established and commonly used strategy by the Global Navigation Satellite System (GNSS) community, the realtime PPP is still under development. We investigate the impact of three tropospheric models and mapping functions regarding position accuracy and convergence time. Keywords GNSS Á Precise point positioning (PPP) Á Tropospheric model Á Mapping functions Á Real-time Á Numerical weather prediction (NWP) Á Least-squares collocation

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