Signal 3: Using Shadow Matching to Improve GPS Accuracy in Cities

Shadowing– Difficult to pinpoint accurate GPS location in dense urban areas due to “shadowing” of buildings and structures, causing signal blockage and reflection.

Shadow Matching — North America has around 30 satellites used for GPS location tracking. Signal-to-noise-ratio (SNR) of each satellite can be used to estimate shadowing: low SNRs indicate a possible signal blockage. “Shadow matching” is comparing satellite SNR to 3D maps of the built environment to provide probabilistic estimates of location data. This term was initially introduced by Dr. Paul Groves in his research conducted at the University College of London (Robust Positioning and Navigation). Uber bought out a startup called ShadowMaps in 2016 to incorporate this method into the Uber app in hopes of reducing ride inefficiencies and driver/rider complications.

This holds enormous potential if integrated into mapping applications (e.g. Google Maps) for providing more accurate transit estimates and improved app-based delivery services, for example.

Next steps — Uber recently launched beta testing of ShadowMaps in 15 cities, and reports an increased accuracy by 2x. Dr. Paul Groves is conducting a pilot study in London as well. It’s only a matter of time until the big mappers hone in on their location accuracy.

Hawkins, A. J. (2018, April 19). How Uber is moving the “blue dot” and improving GPS accuracy in big cities. Retrieved from: https://www.theverge.com/2018/4/19/17252680/uber-gps-blind-spot-shadow-maps

Image source: http://kmj.iis.u-tokyo.ac.jp/gps/e_index.html