HR: 0830h
AN: G11A-0236    [PDF]
TI: Simulation of Lidar System Performance in Terrestrial Mapping Applications
AU: * Pack, R T
EM: rtpack@cc.usu.edu
AF: Utah State University, Center for Advanced Imaging Ladar 4110 Old Main Hill, Logan, UT 84322-4110 United States
AU: Fullmer, R R
EM: rrfullmer@mae.usu.edu
AF: Utah State University, Center for Advanced Imaging Ladar 4110 Old Main Hill, Logan, UT 84322-4110 United States
AB: Anyone who has used terrestrial lidar data in physical science applications has likely observed both systematic and random errors in datasets. An understanding of the potential sources of error is important when applying post-mission filters that remove errors, artifacts and unwanted features - such as vegetation - from lidar "point-cloud" data sets. System error sources typically include, (1) range error associated with transceiver optoelectronics design and atmospheric transmission characteristics, (2) pointing error associated with scanner dynamics, platform instability and GPS/INS readouts. To better understand and anticipate lidar data phenomenology and quality when designing lidar systems and surveys, simulation software has been developed at Utah State University Center for Advanced Imaging Ladar. The simulation focuses on energy-detection lidars common in commercial airborne mapping applications. It accepts as inputs: laser power, pulse width, wavelength, beam divergence and pulse repetition frequency; optics including aperture, field-of-view, and transmission loss; detector characteristics including focal plane array geometry, quantum efficiency, noise-equivalent power, optical efficiency, optical pass band, noise bandwidth, and readout error; scanner dynamics including bandwidth and damping ratio; GPS/INS errors associated with various instrument grades; environmental parameters including aerosol type, visibility, and solar spectral irradiance; scene parameters including backscatter distribution and reflectivity; and trajectories including position, velocity, and attitude. The simulation is designed to be adaptable to a wide variety of lidar system types, environmental settings, and aircraft trajectories over specific terrain models. It was built in MATLAB/Simulink, a convenient environment for computation and data generation, and has many graphical interfaces. Principally funded by the U.S. Naval Air Warfare Center at China Lake, California, it has been proven capable of modeling lidar systems and missions within the U.S. Department of Defense. Examples will be given of simulated range images and point clouds with associated systematic and random errors. The ability of the simulation to predict the density and distribution of laser shots across a terrain model will also be shown. The modeling of lidar swath geometry is of particular use to mission planners and prospective clients who would like to predict the quality and distribution of lidar shots in irregular terrain.
DE: 1224 Photogrammetry
DE: 1294 Instruments and techniques
SC: Geodesy [G]
MN: 2003 Fall Meeting