By topic- Electro-Optic (infrared)
- Radio-Frequency (radar)
- Active-Imagery (laser)
- Satellites Navigation (GNSS)
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Apport de la simulation au dimensionnement des contraintes CEM en haute fréquence dans un environnement complexeCEM 2004 (in french only)
En haute fréquence, la modélisation asymptotique permet de modéliser globalement et efficacement l'environnement électromagnétique nécessaire et l'évaluation des phénomènes de compatibilité électromagnétique intersystème (CEMIS) dans un environnement complexe de grandes dimensions. Cet article décrit la technique de simulation utilisée et présente des résultats qui montrent comment elle peut être appliquée à différents domaines de l'électromagnétisme.
FERMAT a new radar simulation approachRADAR 2004
3D virtual databases are more and more realistic and any kind of terrain and objects can be easily modelled. A new approach in radar simulation is now possible thanks to efficiency in geometrical description and in ray tracing performance. FERMAT code is based on an ElectroMagnetic asymptotic modeling which takes advantage of these improvements for radar simulation.
Low Memory Spectral Photon MappingWSCG 2004 (submitted)
We showed how it is possible to adapt Photon Mapping to a spectral rendering without consuming extra memory while keeping a very good accuracy. Taking into account spectral emission and reflections permitted us to do accurate IR rendering. Our multi-pass method is faster than classical method when photon map fits entirely in memory. We can use an unlimited number of photons. We avoid problems due to photon map caching such as swapping and cache defaults. Thus our method can match very accurate results. This is very interesting for IR rendering, while we can through enough photons to have the noise disappeared.
Multi-pass Density Estimation for Infrared RenderingPacific Graphics 2004 (submitted)
We compute several little particle maps. All these particle maps are global in opposition to the localised particle maps dependent on the geometry of  which means that each particle map stores particles within the entire model. This ensures that the illumination is spread correctly over the scene for each pass and thus that density estimations are correct.We benefit from the speedup of computing multiple small particle maps shown in  without limitation on the mesh complexity because the particle maps are not dependent on the geometry. Unfortunately, when the image size is large (i.e 1024x768 pixels), the time saved while computing and sorting the particle map is lost when rendering due to the number of density estimations needed. Therefore, it is more interesting to compute fewer passes with bigger particle maps when rendering big images. The memory used is constant from one pass to another.