Time-Gated Topographic LIDAR Scene Simulation

Abstract

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model has been developed at the Rochester Institute of Technology (RIT) for over a decade. The model is an established, first-principles based scene simulation tool that has been focused on passive multi- and hyper-spectral sensing from the visible to long wave infrared (0.4 to 14 mum). Leveraging photon mapping techniques utilized by the computer graphics community, a first-principles based elastic Light Detection and Ranging (LIDAR) model was incorporated into the passive radiometry framework so that the model calculates arbitrary, time-gated radiances reaching the sensor for both the atmospheric and topographic returns. The active LIDAR module handles a wide variety of complicated scene geometries, a diverse set of surface and participating media optical characteristics, multiple bounce and multiple scattering effects, and a flexible suite of sensor models. This paper will present the numerical approaches employed to predict sensor reaching radiances and comparisons with analytically predicted results. Representative data sets generated by the DIRSIG model for a topographical LIDAR will be shown. Additionally, the results from phenomenological case studies including standard terrain topography, forest canopy penetration, and camouflaged hard targets will be presented.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2002
Accession Number
ADA431377

Entities

People

  • Daniel D. Blevins
  • John R. Schott
  • Scott D. Brown

Organizations

  • Rochester Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Data Sets
  • Detection
  • Detectors
  • Focal Planes
  • Laser Radar
  • Materials
  • Optical Properties
  • Optics
  • Radar
  • Radiation
  • Ray Tracing
  • Reflectance
  • Scattering
  • Simulations
  • Surface Properties
  • Travel Time

Readers

  • Atmospheric Remote Sensing.
  • Computational Modeling and Simulation
  • Computer Vision.