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Table 4 Performance comparison, single target in clutter edge (S) and multiple targets in clutter (M), \(P=6\)

From: A neural network framework for binary classification of radar detections

Detector (trained on) S: \(P_{\mathrm{D}}\) S: \(P_{\mathrm{FA}}\) M: \(P_{\mathrm{D}}\) M: \(P_{\mathrm{FA}}\)
NN (N) O1, 50x1 0.61 \(2.92\times 10^{-4}\) 0.39 \(4.00\times 10^{-4}\)
NN (N) O2, 50x1 0.78 \(1.89\times 10^{-4}\) 0.65 \(1.95\times 10^{-4}\)
NN (N) O3, 50x1 0.81 \(3.77\times 10^{-3}\) 0.69 \(3.76\times 10^{-3}\)
NN (N) O1, 50x2 0.72 \(1.17\times 10^{-3}\) 0.62 \(1.47\times 10^{-3}\)
NN (N) O2, 50x2 0.80 \(1.62\times 10^{-3}\) 0.70 \(1.76\times 10^{-3}\)
NN (N) O3, 50x2 0.82 \(9.04\times 10^{-3}\) 0.73 \(9.20\times 10^{-3}\)
NN (N+C) O1, 50x1 0.61 \(2.51\times 10^{-5}\) 0.41 \(2.38\times 10^{-5}\)
NN (N+C) O2, 50x1 0.76 \(8.59\times 10^{-6}\) 0.62 \(8.40\times 10^{-6}\)
NN (N+C) O3, 50x1 0.77 \(4.04\times 10^{-7}\) 0.66 \(4.86\times 10^{-7}\)
NN (N+C) O1, 50x2 0.66 \(3.45\times 10^{-5}\) 0.58 \(3.31\times 10^{-5}\)
NN (N+C) O2, 50x2 0.79 \(4.80\times 10^{-5}\) 0.68 \(4.73\times 10^{-5}\)
NN (N+C) O3, 50x2 0.81 \(1.98\times 10^{-5}\) 0.71 \(1.99\times 10^{-5}\)
CMSO-CFAR 0.82 \(1.89\times 10^{-2}\) 0.74 \(1.90\times 10^{-2}\)
SO-CFAR 0.77 \(8.00\times 10^{-3}\) 0.66 \(3.85\times 10^{-3}\)
GO-CFAR 0.60 \(7.63\times 10^{-5}\) 0.14 \(7.03\times 10^{-5}\)