1 research outputs found
Hardware-Accelerated SAR Simulation with NVIDIA-RTX Technology
Synthetic Aperture Radar (SAR) is a critical sensing technology that is
notably independent of the sensor-to-target distance and has numerous
cross-cutting applications, e.g., target recognition, mapping, surveillance,
oceanography, geology, forestry (biomass, deforestation), disaster monitoring
(volcano eruptions, oil spills, flooding), and infrastructure tracking (urban
growth, structure mapping). SAR uses a high-power antenna to illuminate target
locations with electromagnetic radiation, e.g., 10GHz radio waves, and
illuminated surface backscatter is sensed by the antenna which is then used to
generate images of structures. Real SAR data is difficult and costly to produce
and, for research, lacks a reliable source ground truth. This article proposes
a open source SAR simulator to compute phase histories for arbitrary 3D scenes
using newly available ray-tracing hardware made available commercially through
the NVIDIA's RTX graphics cards series. The OptiX GPU ray tracing library for
NVIDIA GPUs is used to calculate SAR phase histories at unprecedented
computational speeds. The simulation results are validated against existing SAR
simulation code for spotlight SAR illumination of point targets. The
computational performance of this approach provides orders of magnitude speed
increases over CPU simulation. An additional order of magnitude of GPU
acceleration when simulations are run on RTX GPUs which include hardware
specifically to accelerate OptiX ray tracing. The article describes the OptiX
simulator structure, processing framework and calculations that afford
execution on massively parallel GPU computation device. The shortcoming of the
OptiX library's restriction to single precision float representation is
discussed and modifications of sensitive calculations are proposed to reduce
truncation error thereby increasing the simulation accuracy under this
constraint.Comment: 17 pages, 7 figures, Algorithms for Synthetic Aperture Radar Imagery
XXVII, SPIE Defense + Commercial Sensing 202