Smartphone precise positioning in urban environments using internal GNSS and IMU sensors

The high level of signal noise and multipath effect errors cannot be neglected when it comes to smartphone-grade GNSS receivers and antennas, and along with frequent carrier-phase measurement discontinuities and losses, pose a challenge for advanced GNSS positioning techniques. In response to these challenges, this work is dedicated to addressing these smartphone positioning obstacles and aims to provide accurate, continuous, and resilient Positioning, Navigation, and Timing (PNT) solutions with a developed smartphone processing software. This research commences with the investigation of smartphone Precise Point Positioning (PPP) performance with external ionospheric constraints. To effectively utilize all satellite measurements in the absence of phase measurements, this work proposes a pseudorange-only measurement enhanced PPP method with single- and dual-frequency combinations. Moreover, to overcome the limitations of both PPP and Real-Time Kinematic (RTK) techniques, a novel PPP/RTK hybridization algorithm with smartphone Inertial Measurement Unit (IMU) integration is proposed. Additionally, this research explores the utilization of the available Galileo HAS corrections for smartphone navigation. Validated through a series of vehicle experiments conducted in realistic driving environments, the results demonstrate a substantial improvement in reducing horizontal rms, improving it from approximately 10 metres to less than 1.5 metres compared to traditional Single Point Positioning (SPP) solutions, showing a noteworthy improvement in smartphone-based mobile positioning for mass-market applications.

Author dc:creator

• Yi, Ding

Advisor dc:contributor.advisor

• Bisnath, Sunil

• Remote sensing
• Aerospace engineering
• Engineering

Statement dc:rights

• Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.

Language dc:language

en

Handle dc:identifier.uri

https://hdl.handle.net/10315/42182

OAI identifier oai:identifier

oai:yorkspace.library.yorku.ca:10315/42182