## 4 Results and Discussion
### Influence of Measurement Accuracy on Discrimination Performance  
This experiment simulates the discrimination performance of the DVB method with different velocity and angle measurement accuracies. Experimental parameters are set as shown in Table 1, and the velocity and angle accuracy of T/R, R\({}_{1}\) and R\({}_{2}\) stations are the same. During the simulation, the velocity and angle measurement accuracy of the multistatic radar system are changed, respectively, and other parameters are kept unchanged. The desired misjudgment probability of the physical target is also set as \(P_{PT}^{\prime}=0.01\). The discrimination threshold can be obtained from Equation (31) as \(\epsilon=6.63\). In Figure 6, the discrimination probabilities of targets \(P_{PT}\) and \(P_{FT}\) are given as a function of deception velocity \(v_{D}\). The curves correspond to different velocity measurement accuracy \(\sigma_{v}\), where \(\sigma_{v}=1\) m/s, 2 m/s and 4 m/s. All performance curves are obtained by averaging over 5000 independent Monte Carlo experiments at each value of \(v_{D}\). It can be seen from Figure 5(a) that when the value of deception velocity is small, the radar velocity measurement accuracy has a significant impact on the discrimination probability of the physical target, and the higher the velocity measurement accuracy, the better the discrimination performance for the physical target. However, with the increase in deception velocity, the discrimination probability of the physical target gradually increases and remains around the expected discrimination probability of 99%. For the three cases of velocity measurement accuracy, when the deception velocity is not less than 100 m/s, the discrimination probability of the physical target has reached the expected level, and then the constant misjudgment property is maintained for the physical target. Compared with the physical target, the discrimination performance for active false targets is very sensitive to the velocity measurement accuracy as shown in Figure 5(b). The higher the measurement accuracy of the deception velocity, the higher the discrimination probability of the active false target. This is because the order of magnitude of the target velocity is relatively small, and the velocity error of a small value will cause a large deviation in the calculated velocity vector. Figure 5: Discrimination performance of four methods versus different SNR/JNR. In Figures 7 and 8, the discrimination probabilities of targets \(P_{PT}\) and \(P_{FT}\) are given as a function of deception velocity \(v_{D}\). The curves correspond to different azimuth and pitch angle measurement accuracy \(\sigma_{\alpha}\) and \(\sigma_{\beta}\), where the range of \(\sigma_{\alpha}\) and \(\sigma_{\beta}\) are 0.10\({}^{\circ}\), 0.50\({}^{\circ}\), 1.00\({}^{\circ}\) and 1.50\({}^{\circ}\). All performance curves are obtained by averaging over 5000 independent Monte Carlo experiments at each value of \(v_{D}\). The simulation results show that the accuracy of angle measurement does not affect the discrimination performance dramatically. However, in the overall trend, the greater the accuracy of angle measurement, the better the discrimination performance of the proposed method. Comparing Figure 7 with Figure 8, the measurement accuracy of azimuth angle has a larger effect than that of pitch angle on the discrimination performance. This is because the variation of the radial velocity caused by the azimuth angle change is greater than that caused by an equivalent change of pitch angle. In the derivation process in Section 3.2, the receivers are assumed to be located on the common baseline. However, the insensitivity property of the performance to the azimuth and pitch angle makes the proposed method suitable for the case that receiver stations can be distributed within a certain area around the common baseline rather than loca  
Figure 6: Discrimination performance of proposed method versus different velocity measurement accuracy.