GPS World, March 2017

SIMULATION INTEGRATION simulation 50 1400 second long different trajectories with flat areas are generated with different platform attitude velocity or acceleration As can be seen from the figure compared to other integrated navigation methods the CLT method greatly improves the accuracy of navigation During 8426 of the simulation period CLT could maintain the position error less than 3 meters the rate with error that is larger than 15 meters is 12 For the TC method due to the frequent divergence of the data fusion filter most of the position estimates are not available In addition after flying above a flat area the voting based constellation integrated method has poor matched point accuracy and successfully matched rate due to large INS drift error which makes lidar unable to calibrate the INS When using the constellation based method during only 3235 of the simulation period the 32 GPS WORLD WWW GPSWORLD COM MARCH 2017 FIGURE 10 Position error distribution when using four different lidar INS integrated navigation method error is maintained in 3 meters and most of the period 549 the position error is between 3 to 15 meters CONCLUSION We propose a new lidar matching algorithm based on SIFT which does not rely on the INS output data to generate measured DEM data and can adaptively change the threshold of the SIFT algorithm to generate optimal matching between the point cloud and the DEM Through verification of simulation the algorithm is compared with traditional lidar INS integrated navigation methods based on comparing achieved accuracies in estimating positon speed and attitude Simulation results show that the SLPF algorithm has better reliability for feature points matching and robustness against the platform attitude than the traditional algorithms The CLT method improves trajectory estimation accuracy especially when flying over moderately undulating terrain or flying with large roll or pitch angles ACKNOWLEDGMENT This article is based on a paper presented at the ION International Technical Meeting January 2017 This research used an open source GNSS INS simulator based on Matlab developed by Gongmin Yan of Northwestern Polytechnical University China HAOWEI XU is a Ph D student at Northwestern Polytechnical University where he received an M Sc in Information and Communication Engineering He is a visiting scholar at The Ohio State University BAOWANG LIAN is a professor at Northwestern Polytechnical University where he is also director of the Texas Instruments DSPs Laboratory CHARLES K TOTH is a senior research scientist at the Ohio State University Center for Mapping He received a Ph D in electrical engineering and geo information sciences from the Technical University of Budapest Hungary DOROTA A BRZEZINSKA is a professor in geodetic science and director of the Satellite Positioning and Inertial Navigation SPIN Laboratory at The Ohio State University FIGURE 9 Data fusion results using two different integrated algorithms a above Position determination error b below velocity determination error c bottom attitude determination error