Research Article
Deep Anomaly Detection with Attention (DADA): A Novel Approach for Identifying Multipath Interference in Radar Signals
Table 2
Performance metrics for the seven methods (test set with two multipath signals).
| Method | LFM NLFM (LN) | LFM BPSK (LB) | LFM QPSK (LQ) | P | R | F1 | P | R | F1 | P | R | F1 |
| CCF | 0.639 | 1.000 | 0.779 | 0.671 | 0.997 | 0.802 | 0.667 | 1.000 | 0.800 | SC | 0.659 | 1.000 | 0.794 | 0.591 | 1.000 | 0.743 | 0.660 | 1.000 | 0.795 | WRFCCF | 0.675 | 0.950 | 0.789 | 0.610 | 0.700 | 0.651 | 0.621 | 0.927 | 0.744 | AnoGAN | 0.755 | 0.902 | 0.822 | 0.520 | 0.942 | 0.670 | 0.528 | 0.992 | 0.689 | EGBAD | 0.673 | 0.965 | 0.793 | 0.503 | 0.995 | 0.668 | 0.540 | 0.995 | 0.700 | GANomaly | 0.731 | 1.000 | 0.844 | 0.541 | 0.553 | 0.547 | 0.576 | 0.657 | 0.614 | DADA | 0.910 | 0.962 | 0.936 | 0.711 | 0.990 | 0.828 | 0.911 | 0.848 | 0.878 |
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