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Technology you can trust

KAISAR

KAISAR

Physics-based SAR simulator for:

  • Generating training dataset for AI/ML/DL
  • Creating database for Automatic Target Recognition
  • Perform system design and performance analysis
  • Create SAR datasets for algorithm developments

Applications:

  • To create a structured dataset for deep object detection and ATR database
    1. Enabling Deep/Machine Learning on SAR data for Target Detection with large training datasets (10k + scenes)
    2. Providing data augmentation capabilities for ATR database generation
  • To allow fast and accurate3D RCS map simulations (EM-Solver)
    1. Using state of the art GPU-accelerated ray-tracing methods for near-field reflection and diffraction simulation (GO + UTD)
    2. Using asymptotic HF methods for far-field backscattering from illuminated objects (PO + PTD)
  • Provide an accurate and fast SAR RAW data generator
    1. Modelling SAR system and platform trajectory
    2. Use of innovative GPU-accelerated Reverse Back-Projection algorithm
  • Focus SAR images and provide target labelling for deep object detection and ATR database
    1. Powered by GPU-accelerated Global Back-Projection algorithm
    2. Target labelling infrastructure (also in the range compressed data)
    3. Dataset structure based on xView dataset
    4. SAR images over targets with data augmentation

Physics-based SAR simulator for:

  • Generating training dataset for AI/ML/DL
  • Creating database for Automatic Target Recognition
  • Perform system design and performance analysis
  • Create SAR datasets for algorithm developments

Applications:

  • To create a structured dataset for deep object detection and ATR database
    • Enabling Deep/Machine Learning on SAR data for Target Detection with large training datasets (10k + scenes)
    • Providing data augmentation capabilities for ATR database generation
  • To allow fast and accurate3D RCS map simulations (EM-Solver)
    • Using state of the art GPU-accelerated ray-tracing methods for near-field reflection and diffraction simulation (GO + UTD)
    • Using asymptotic HF methods for far-field backscattering from illuminated objects (PO + PTD)
  • Provide an accurate and fast SAR RAW data generator
    • Modelling SAR system and platform trajectory
    • Use of innovative GPU-accelerated Reverse Back-Projection algorithm
  • Focus SAR images and provide target labelling for deep object detection and ATR database
    • Powered by GPU-accelerated Global Back-Projection algorithm
    • Target labelling infrastructure (also in the range compressed data)
    • Dataset structure based on xView dataset
    • SAR images over targets with data augmentation

Downloads & Brochures

  • KAISAR Brochure

Italy

Rocca D’Evandro

Italy

Milano

The Netherlands

Leiden

Singapore

Singapore

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