Communication Dans Un Congrès Année : 2025

Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoders

Résumé

This paper presents a novel approach to radar target detection using Variational AutoEncoders (VAEs). Known for their ability to learn complex distributions and identify out-ofdistribution samples, the proposed VAE architecture effectively distinguishes radar targets from various noise types, including correlated Gaussian and compound Gaussian clutter, often combined with additive white Gaussian thermal noise. Simulation results demonstrate that the proposed VAE outperforms classical adaptive detectors such as the Matched Filter and the Normalized Matched Filter, especially in challenging noise conditions, highlighting its robustness and adaptability in radar applications.

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Dates et versions

hal-04975012 , version 1 (05-03-2025)

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Y A Rouzoumka, E Terreaux, C Morisseau, J.-P Ovarlez, C Ren. Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoders. ICASSP, IEEE, Apr 2025, Hyderabad, India. ⟨hal-04975012v1⟩
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