GPS World, February 2019

MAPPING NEW MAP METHOD OPENS UP PARKING CONTINUOUS ENVIRONMENT MAPPING FOR ENHANCED LOW COST URBAN NAVIGATION COLLECTIVELY RECORDED CONTEXT DATA BY MANY IDENTICAL PLATFORMS gather similar sensor readings when operating in a given area Further processing integrates the data with a map and feeds the summarized results to a user C omplex dynamic urban environments comprise BY Ivan Smolyakov Evgeny Klochikhin and Richard B Langley millions of devices with localization capabilities While GNSS remains a primary positioning tool its performance is subject to significant degradation from blocked signals multipath and non line of sight NLOS signal reception In aided navigation a positioning filter with GNSS measurements integrates data from various sensors and correction streams to compensate for these disadvantages Low cost platforms are limited with the variety and quality of sensors on board as well as by processor performance and battery capacity Positioning routines must be computationally light energy efficient and make the most productive use of available data One new research area covers use of crowd sourced GNSS data Many vehicles now include some type of native wireless connection capability which could be complemented by a designated third party device The growth in connectivity brings an opportunity to access a stream of sensor data produced by a high number of devices operating in a localized urban area Here we explore the idea of creating a GNSS signal strength map using the connected vehicle GNSS data stream and then use the map as statistical information for Kalman filter parameters tuning This approach improves filter reaction to the environment and produces a positioning accuracy improvement SYSTEM ARCHITECTURE C N 0 levels of reflected and diffracted signals are more likely to be lower than that of the LOS signals We propose that the C N 0 level averaged during a given period among all satellites tracked in a given area would correlate with a higher probability of multipath contaminated and NLOS signal reception A sufficient number of C N 0 readings associated with a given space time cube should be collected to compute the statistics populating the signal strength map However the city environment does not remain static new construction occurs traffic congestion shifts and so on Therefore the C N 0 space time statistics must be continuously updated in real time to reflect these changes Additionally the solution must be highly scalable as the market of connected vehicles 46 GPS WORLD WWW GPSWORLD COM FEBRUARY 2019 Photo Norbert Schnidler