title: Enhancing positioning accuracy in urban terrain by fusing data from a GPS receiver, inertial sensors, stereo-camera and digital maps for pedestrian navigation.
abstract: The paper presents an algorithm for estimating a pedestrian location in an urban environment. The algorithm is based on the particle filter and uses different data sources: a GPS receiver, inertial sensors, probability maps and a stereo camera. Inertial sensors are used to estimate a relative displacement of a pedestrian. A gyroscope estimates a change in the heading direction. An accelerometer is used to count a pedestrian's steps and their lengths. The so-called probability maps help to limit GPS inaccuracy by imposing constraints on pedestrian kinematics, e.g., it is assumed that a pedestrian cannot cross buildings, fences etc. This limits position inaccuracy to ca. 10 m. Incorporation of depth estimates derived from a stereo camera that are compared to the 3D model of an environment has enabled further reduction of positioning errors. As a result, for 90% of the time, the algorithm is able to estimate a pedestrian location with an error smaller than 2 m, compared to an error of 6.5 m for a navigation based solely on GPS.
authors.affiliation: Institute of Electronics, Technical University of Lodz, Lodz, Poland. przemyslaw.baranski@p.lodz.pl
authors.forename: Baranski
authors.initials: B
authors.lastname: Przemyslaw
authors.forename: Strumillo
authors.initials: S
authors.lastname: Pawel
mesh_terms: D000465:Algorithms; D002947:Cities; D003867:Depth Perception; D040362:Geographic Information Systems / Q000295:instrumentation*; D006801:Humans; D008377:Maps as Topic; D010781:Photography / Q000295:instrumentation*; D011336:Probability; D058998:Remote Sensing Technology / Q000295:instrumentation*; D014495:Universities; D016138:Walking