# High Fidelity RF Clutter Modeling and Simulation

arXiv: https://arxiv.org/abs/2202.05666 · HTML: https://mlsanity.com/paper/2202.05666/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Feb 2022.

## Built on by (most cited first, 3 of 3)

- [Data-Driven Target Localization Using Adaptive Radar Processing and Convolutional Neural Networks](https://mlsanity.com/paper/2209.02890/) (2022)
- [Subspace Perturbation Analysis for Data-Driven Radar Target Localization](https://mlsanity.com/paper/2303.08241/) (2023)
- [Data-Driven Target Localization: Benchmarking Gradient Descent Using the Cramer-Rao Bound](https://mlsanity.com/paper/2401.11176/) (2024)

## Abstract (arXiv)

In this paper, we present a tutorial overview of state-of-the-art radio frequency (RF) clutter modeling and simulation (M&S) techniques. Traditional statistical approximation based methods will be reviewed followed by more accurate physics-based stochastic transfer function clutter models that facilitate site-specific simulations anywhere on earth. The various factors that go into the computation of these transfer functions will be presented, followed by several examples across multiple RF applications. Finally, we introduce a radar challenge dataset generated using these tools that can enable testing and benchmarking of all cognitive radar algorithms and techniques.