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Out-of-Distribution Radar Detection with Complex VAEs: Theory, Whitening, and ANMF Fusion

arXiv 2601.18677 ↗First posted 26 Jan 2026stat.ML cs.LGcited by 0

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Abstract (arXiv)

We investigate the detection of weak complex-valued signals immersed in non-Gaussian, range-varying interference, with emphasis on maritime radar scenarios. The proposed methodology exploits a Complex-valued Variational AutoEncoder (CVAE) trained exclusively on clutter-plus-noise to perform Out-Of-Distribution detection. By operating directly on in-phase / quadrature samples, the CVAE preserves phase and Doppler structure and is assessed in two configurations: (i) using unprocessed range profiles and (ii) after local whitening, where per-range covariance estimates are obtained from neighboring profiles. Using extensive simulations together with real sea-clutter data from the CSIR maritime dataset, we benchmark performance against classical and adaptive detectors (MF, NMF, AMF-SCM, ANMF-SCM, ANMF-Tyler). In both configurations, the CVAE yields a higher detection probability Pd at matched false-alarm rate Pfa, with the most notable improvements observed under whitening. We further integrate the CVAE with the ANMF through a weighted log-p fusion rule at the decision level, attaining enhanced robustness in strongly non-Gaussian clutter and enabling empirically calibrated Pfa control under H0. Overall, the results demonstrate that statistical normalization combined with complex-valued generative modeling substantively improves detection in realistic sea-clutter conditions, and that the fused CVAE-ANMF scheme constitutes a competitive alternative to established model-based detectors.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 55 references that are in the map. First posted on arXiv 26 Jan 2026.

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15 of 55 references.

References · 15

  1. 2020Energy-based Out-of-distribution Detectioncited by 1,296
  2. 2021Generalized Out-of-Distribution Detection: A Surveycited by 796
  3. 2021Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancycited by 387
  4. 2022TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Datacited by 211
  5. 2020Stochastic Normalizing Flowscited by 156
  6. 2020SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flowscited by 71
  7. 2021Contrastive Out-of-Distribution Detection for Pretrained Transformerscited by 70
  8. 2020Anomaly detection through latent space restoration using vector-quantized variational autoencoderscited by 45
  9. 2020Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimationcited by 24
  10. 2022Transformer-based out-of-distribution detection for clinically safe segmentationcited by 16
  11. 2022On Out-of-Distribution Detection for Audio with Deep Nearest Neighborscited by 9
  12. 2023MCROOD: Multi-Class Radar Out-Of-Distribution Detectioncited by 9
3 more
  1. 2023HOOD: Real-Time Human Presence and Out-of-Distribution Detection Using FMCW Radarcited by 4
  2. 2023A Deep Representation Learning-based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencodercited by 3
  3. 2025Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoderscited by 3

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