Paper Info
Title
Matching Raw GPS Measurements on a Navigable Map Without Computing a Global Position
Abstract
Map matching means determining the location of a mobile with respect to a road network description stored in a digital map. This problem is usually addressed using Global Positioning System (GPS)-like fixes. Unfortunately, there are many situations in urban areas where few satellites are visible because of outages due to tall buildings. In this paper, map matching is solved using raw GPS measurements (pseudoranges and Doppler measurements), avoiding the necessity to compute a global position. The problem is formalized in a general Bayesian framework to handle noise, which can perform multihypothesis map matching when there is not enough information to make unambiguous decisions. This tightly coupled GPS–map fusion has to simultaneously cope with identifying the road and estimating the mobile's position on that road. A marginalized particle filter is proposed to efficiently solve this hybrid estimation problem. Real experimental results are reported to show that this approach can be initialized with fewer than four satellites. It can also track the location with only two satellites once the road selection has been solved.
Year
DOI
Venue
2012
10.1109/TITS.2012.2186295
IEEE Transactions on Intelligent Transportation Systems
Keywords
Field
DocType
Bayes methods,Doppler measurement,Global Positioning System,mobile radio,particle filtering (numerical methods),Doppler measurement,general Bayesian framework,global position computation,hybrid estimation problem,marginalized particle filter,mobile location determination,mobile position estimation,multihypothesis digital map matching,noise handling,pseudorange measurement,raw GPS measurement,raw Global Positioning System measurement,road identification,road network description,satellite,tightly coupled GPS-map fusion,Global Positioning Systems (GPSs),hybrid state estimation,map matching,particle filtering
Mobile radio,Computer vision,Satellite,Simulation,Particle filter,Global Positioning System,Artificial intelligence,Estimation theory,Engineering,Doppler effect,Map matching,Bayesian probability
Journal
Volume
Issue
ISSN
13
2
1524-9050
Citations 
PageRank 
References 
13
0.76
14
Authors
2
Name
Order
Citations
PageRank
Clément Fouque1201.76
Philippe Bonnifait245255.82