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conditioning and PPP processing of smartphone GnSS measurements in realistic environments

Satellite navigation 2021年第1期2卷 141-157页

作者： Ganga Shinghal Sunil Bisnath Department of Earth and Space Science and Engineering Lassonde School of EngineeringYork UniversityTorontoCanada

Smartphones typically compute position using duty-cycled Global navigation Satellite System (GnSS) L1 code measurements and Single Point Positioning (SPP) processing with the aid of cellular and other measurements. This internal positioning solution has an accuracy of several tens to hundreds of meters in realistic environments (hand-held, vehicle dashboard, suburban, urban forested, etc.). With the advent of multi-constellation, dual-frequency GnSS chips in smartphones, along with the ability to extract raw code and carrier-phase measurements, it is possible to use Precise Point Positioning (PPP) to improve positioning without any additional equipment. This research analyses GnSS measurement quality parameters from a Xiaomi MI 8 dual-frequency smartphone in varied, realistic environments. In such environments, the system suffers from frequent phase loss-of-lock leading to data gaps. The smartphone measurements have low and irregular carrier-to-noise (c/n0) density ratio and high multipath, which leads to poor or no positioning solution. These problems are addressed by implementing a prediction technique for data gaps and a c/n0-based stochastic model for assigning realistic a priori weights to the observables in the PPP processing engine. Using these conditioning techniques, there is a 64% decrease in the horizontal positioning Root Mean Square (RMS) error and 100% positioning solution availability in sub-urban environments tested. The horizontal and 3D RMS were 20 cm and 30 cm respectively in a static open-sky environment and the horizontal RMS for the realistic kinematic scenario was 7 m with the phone on the dashboard of the car, using the Swiftnav Piksi Real-Time Kinematic (RTK) solu-tion as reference. The PPP solution, computed using the YorkU PPP engine, also had a 5-10% percentage point more availability than the RTK solution, computed using RTKLIB software, since missing measurements in the logged file cause epoch rejection and a non-continuous solution, a

关键词： PPP Smartphone Realistic environment Prediction c/n0-based stochastic modeling Internal phone solution Positioning solution comparison

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