GPS World, March 2016
GNSS PHOTO MATCHING ADVERTISER INDEX COMPANIES FEATURED IN THIS ISSUE MARCH 2016 WWW GPSWORLD COM GPS WORLD 57 BETTER NAV FOR UAVS SELF DRIVING CARS ADVANCED MULTI RECEIVER VECTOR TRACKING FOR POSITIONING A LAND VEHICLE by Yuting Ng and Grace Xingxin Gao University of Illinois The states of multiple receivers in a network are jointly tracked through the states of the receiver network a rigid body carrying multiple GPS antennas The relative antenna geometry and baselines remain unchanged can be estimated in advance and used as prior information This reduces the number of states required to describe the network to reference position clock bias velocity clock drift and attitude Once estimated and filtered this information augments the vector tracking within each receiver reducing the overall search space to the states of the network This method offers increased robustness due to information redundancy Evaluation experiments were conducted on a road vehicle Presented at ION GNSS 2015 ADVERTISER PAGE S AUVSI 41 CAST NAVIGATION 15 CHC NAVIGATION 45 COMNAV TECHNOLOGY 37 EUROPEAN NAVIGATION CONFERENCE 42 EVE ENERGY INSIDE FRONT COVER IFEN 8 9 25 INSTITUTE OF NAVIGATION ION 44 MICROSEMI 4 NOVATEL BACK COVER RACELOGIC 13 ADVERTISER PAGE S SBG SYSTEMS 11 SEPTENTRIO 19 SKYDEL SOLUTIONS 7 SPECTRACOM 5 SPIRENT FEDERAL INSIDE BACK COVER SWIFT NAVIGATION 43 TALLYSMAN 27 TELEORBIT 39 TERRAGO 35 UNICORE 21 COMMUNICATIONS A n urban positioning te chniqu e for personal location in environments with poor satellite geometry and or multipath uses photos taken on a smartphone The authors combine GNSS with a 3D map camera accelerometer and magnetic sensor on a smartphone to improve positioning accuracy An experiment in an urban canyon used a GNSS receiver and a smartphone to collect data from multiple locations The likelihood of candidate positions are determined based on an image matching technique comparing the captured photo and a virtual photo from Google Earth simulated based on the candidate position camera attitude and 3D map The likelihood of a candidateposition increases when it is near the true position By Taro Suzuki Waseda University Japan and Nobuaki Kubo Tokyo University of Marine Science and Technology Presented at ION GNSS 2015 in Tampa Florida estimating likelihood of position using 3D map and photo taken with a smartphone
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