|Abstract:||GNSS augmentation techniques for mining, civil construction and landfill have evolved from single ad-hoc radio Real Time Kinematic (RTK) bases, to subscription-based Network RTK and Precise Point Positioning (PPP) delivered by L-band satellite communication covering regional and global areas. While RTK is traditionally used in these industries for precise positioning, it is possible to use local ionospheric corrections to combine both PPP and RTK methods in a State-Space Representation (SSR), or a loosely termed PPP-RTK type system . The PPP approach promises to deliver centimeter level accuracies and have the potential to be used in selected applications in which an instantaneous convergence time is not critical. One such application in mining, civil construction and landfill is dozer push or bulk material earthmoving for dozers with automated machine guidance (AMG) and automated machine control (AMC) where vertical tolerances of less than 10 cm (2sigma 95%) are sufficient. In this paper, we present the experimental results from field trials carried out in collaboration with the Australian Cooperative Research Centre for Spatial Information (CRCSI), Japan Aerospace Exploration Agency (JAXA), RMIT University, EnergyAustralia and Position Partners; where RTK, PPP with Ambiguity Resolution (PPP-AR) and PPP-RTK solutions were compared on board a dozer performing routine mining operations in the La Trobe valley region of Victoria, Australia. The PPP-AR and PPP-RTK solutions were generated from RTKLIB software using the French Centre National d'Études Spatiales (CNES) CLK91 real-time correction stream and ionospheric corrections calculated for a regional network . Different augmentation delivery methods were validated: UHF radio (for RTK only), Internet Protocol and the L6 signal (formerly known as L-Band Experimental, LEX) transmitted by the Quasi-Zenith Satellite System (QZSS) . The aim of the trials was to evaluate the performance of PPP realtime solutions and delivery methods for use in machine control and guidance applications. Field data was collected using a GNSS antenna mounted on the machine that was split into different GNSS receivers: Topcon Hiper M and Javad Delta-3 with a QZSS-LEX decoder. Three trials were conducted under real operating conditions with varying scenarios of obstructions, batter slopes and operating speed. The PPP-AR and PPP-RTK results were compared to RTK and postprocessed kinematic positioning solutions, which were used as ground truth. The resulting navigation performance for PPP-AR and PPP-RTK methods was analyzed in terms of accuracy, convergence time and stability of the solution. The real-time tests show that the PPP-RTK solutions converged to 10 cm horizontal accuracy within 6 min, while the vertical component converged within 20 min. The stability of the solution was determined by the percentage of time the solutions are within 10 cm of the ground truth after convergence period, and in which case 95% for the horizontal component and 86% for vertical component. The real-time tests indicate that in ideal conditions, PPP-RTK convergence times and accuracy can meet the requirements of machine control dozer push for mining applications. However additional work is still required to further improve the solution convergence period and provide integrity measures to indicate the reliability of the PPP-RTK solutions. It is envisaged that by providing a more robust solution, there is potential for PPP-RTK like augmentation to be extended and applied to other applications in the civil construction and mining industries.|
Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
|Pages:||2235 - 2243|
|Cite this article:||
Elneser, Luis, Choy, Suelynn, Harima, Ken, Millner, James, "Real-Time GPS PPP-RTK Experiments for Mining Applications using Quasi-Zenith Satellite System (QZSS) Augmentation Signal," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 2235-2243.
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