用复数变分自编码器检测雷达异常信号，提升复杂环境识别能力
Latent-space metrics for Complex-Valued VAE out-of-distribution detection under radar clutter
- 基于复数空间的变分自编码器设计新检测指标
- 在实测与仿真数据上验证性能，复数重建误差表现最优
- 适合雷达信号异常检测场景，尤其适用于复杂杂波环境
我们研究了复数变分自编码器（CVAE）在复杂雷达环境下进行离群检测的应用。提出了多种检测指标：CVAE的重构误差（CVAE-MSE）、基于潜在空间的度量（马氏距离、相对熵KLD），并与经典ANMF-Tyler检测器（ANMF-FP）进行了对比。所有检测器在合成与实测雷达数据上的性能均被分析，揭示了各方法的优势与局限。
原文摘要 · Abstract (English)
We investigate complex-valued Variational AutoEncoders (CVAE) for radar Out-Of-Distribution (OOD) detection in complex radar environments. We proposed several detection metrics: the reconstruction error of CVAE (CVAE-MSE), the latent-based scores (Mahalanobis, Kullback-Leibler divergence (KLD)), and compared their performance against the classical ANMF-Tyler detector (ANMF-FP). The performance of all these detectors is analyzed on synthetic and experimental radar data, showing the advantages and the weaknesses of each detector.
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