?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Kinematic+GNSS+Shadow+Matching+Using+Particle+Filters&rft.creator=Wang%2C+L&rft.description=Student+Paper+Award+Winner.+The+poor+performance+of+GNSS+user+equipment+in+urban+canyons+is+a+well-known+problem+and+is+particularly+inaccurate+in+the+cross-street+direction.+However%2C+the+accuracy+in+this+direction+greatly+affects+many+applications%2C+including+vehicle+lane+identification+and+high-accuracy+pedestrian+navigation.+Shadow+matching+was+proposed+to+help+solve+this+problem+by+using+information+derived+from+3D+models+of+buildings.+Though+users+of+GNSS+positioning+typically+move%2C+previous+research+has+focused+on+static+shadow-matching+positioning.+In+this+paper%2C+for+the+first+time%2C+kinematic+shadow-matching+positioning+is+tackled.+Kalman+filter+based+shadow+matching+is+proposed+and+also%2C+in+order+to+overcome+some+of+its+predicted+limitations%2C+a+particle+filter+is+proposed+to+better+solve+the+problem.&rft.publisher=The+Institute+of+Navigation&rft.date=2014-09-12&rft.type=Proceedings+paper&rft.source=+++++In%3A++Proceedings+of+the+27th+International+Technical+Meeting+of+The+Satellite+Division+of+the+Institute+of+Navigation+(ION+GNSS%2B+2014).++(pp.+1907+-+1919).++The+Institute+of+Navigation%3A+Manassas%2C+US.+(2014)+++++&rft.format=application%2Fpdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F1421172%2F1%2FGNSS14-0181.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F1421172%2F&rft.rights=open