GPU-accelerated Computation of 3D Laser Radar Range Imaging of Arbitrary Coarse Targets

Abstract

We report here a backscattering model of average signal power function (SPF) for laser radar 3D range imagery obtained by arrays of detectors for arbitrary coarse targets. The model relates the average power seen by the receiver with laser pulse, target shape, optical scattering properties of surface material, incidence angle and other factors. The optical scattering property of the material is characterized by bidirectional reflectance distribution function (BRDF). The model can be used for demonstration of 3D laser radar system and can also be used to generate library of model data sets for automatic target recognition (ATR). Finally, Compute Unified Device Architecture (CUDA) is introduced for parallelizing these algorithms. The acceleration reaches 56 times speedup on single Fermi-generation NVIDIA GTX 480 as compared to the traditional CPU version of code on Intel i7 930 CPU.