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Autonomy Technology Research (ATR) Center Summer Program



High Fidelity RF Modeling and Simulation Workshop, August 10, 2020 [NEW DATE]


Date: AUGUST 10, 2020
Time: 9:30 a.m.–5:30 p.m. EST
Location: Virtual Zoom Meeting


About the Workshop

The inaugural High-Fidelity RF Modeling and Simulation Workshop will cover a wide range of topics related to state-of-the-art theoretical modeling of RF clutter and targets along with a real-time experience of using state of the art RF modeling and simulation (M&S) tools.

With increasing developmental flight testing costs and the shortage of representative data sets, it is critical to develop and use high-fidelity site-specific M&S tools to undertake a performance assessment of candidate radar signal processing algorithms in a representative environment. The tools discussed in the workshop can be used to model various scenarios like SAR, GMTI, and communications.

Tutorial examples encompassing these applications will be covered in this workshop. The attendees will get an opportunity to try these tools to generate representative RF data cubes. As part of the workshop, we will also distribute challenge radar datasets that can be used to assess performance of candidate radar signal processing algorithms. Such a common dataset is essential to benchmark performance.

Please join us to learn and discuss the latest advances in the field of high fidelity site specific RF M&S. All workshop discussions will be Distribution A (Approved for public release with unlimited distribution).


General Co-Chairs
  • Muralidhar Rangaswamy, Ph.D.
  • Joseph R. Guerci, Ph.D.
Technical Co-Chairs
  • Sandeep Gogineni, Ph.D.
  • Brian Rigling, Ph.D.
Publicity Chairman
  • Gregory Carter
Administrative Support
  • Beverly Wood


Topics covered:

  • Cognitive Fully Adaptive Radar (CoFAR) and the need for high-fidelity M&S tools
  • Recent advances in site-specific RF clutter models and their comparison with traditional approximate statistical models
  • Electromagnetic scattering models for extended radar targets
  • Application of the state of the art M&S tools for SAR and GMTI
  • Challenge radar datasets that can be used for algorithm performance analysis and benchmarking