## 4 Experimental Results
### Simulation Results
#### 4.1.1 One Vehicle  
In the first simulation experiment, we illustrate the sensing effectiveness of the designed waveform and uniform waveform by the DFT-based method. Consider one car coming towards the communication station with \(r=100\) m and \(v=60\) km/h. Figure 11 shows the range-velocity map of three waveforms with the DFT-based method, where the red rectangle presents the real parameter of the real car, the red ellipse presents the ambiguous parameter, and the red line presents the unambiguity velocity region. Obviously, the uniform sensing waveform can detect the object unambiguously. In Figure 11b,c, we can see that the range-velocity map of the \(2T_{r}\) and \(3T_{r}\) sensing waveforms shows velocity ambiguously. Fortunately, the real velocity has the minimum bias between the range-velocity map of \(2T_{r}\) and \(3T_{r}\). Hence, it can solve the real velocity with the CRT method easily. Obviously, it can realize traffic detection and parameter estimation with the corresponding signal processing method under the designed sensing waveform. Then, in the next simulation experiment, we illustrate the estimated performance of the designed sensing waveform with different signal processing methods. It assumes that the parameters of the detected car are the same as the last experiment, and 500 independent Monte Carlo experiments are performed under different signal-to-clutter-plus-noise ratios (SCNRs). The SCNR is defined as  
\[\text{SCNR}=10 lg\frac{P_{s}}{P_{c}+P_{n}}, \tag{30}\]  
where \(P_{s}\), \(P_{c}\), \(P_{n}\) denote the power of signal, clutter, and noise, respectively. Figure 12a is the detection probability of the designed waveform with the DFT, IAA, and OMP methods. It can been seen that the probability of detection (Pd) increases with the increase in SCNR, and every signal processing method can achieve Pd \(>95\%\) while \(\text{SCNR}\geq-20\) dB. The detection probability of the designed dual-PRF sensing waveform has some SCNR loss compared with that of uniform sensing. It can be seen that the detection probability of the designed dual-PRF sensing waveform has 5 dB SCNR loss compared with that of uniform sensing with Pd = 0.9. And it is caused by less sensing symbols of the designed waveforms than that of the uniform one. Figure 12b,c illustrates the RMSEs of range and velocity, respectively. It can be seen from Figure 12b that the RMSE of the range tends to be consistent under every waveform because of the same range estimation method for each waveform. Unlike range estimation, the RMSE of velocity illustrates different results. It can be seen from Figure 12c that the estimation performance of the designed sensing waveform with the DFT method is poorer compared with the uniform one because of the use of less sensing symbols in the Doppler dimension. The velocity RMSE of the designed waveform is about 0.3 m/s (equal to 1.08 km/h) and it is one resolve cell \(\Delta v=2.08\) km/h. The RMSEs of velocity are almost similar under each sensing waveform with the IAA and the OMP method, respectively. Actually, the IAA and the OMP methods improve estimation performance using nonlinear methods by solving an optimization problem. On one hand, they cost more in computing complexity. On the other hand, they need higher SCNR to realize accuracy reconstruction, and this can be verified in Figure 12a. It can be seen from the figure that there are obviously more SCNR loss by using the IAA and the OMP methods to the same waveform. It can be seen from the figure that there are obviously more SCNR losses by using the IAA and the OMP methods for the same waveform. For better or worse, the RMSEs of range and velocity are all in one solve cell, and these can satisfy the road traffic monitoring [40]. Hence, the designed sensing waveform can satisfy the traffic detection scenario with the common signal processing methods, such as the DFT, IAA, and OMP methods. Figure 11: Estimated range-velocity spectrum. (**a**) Uniform Waveform. (**b**) Dual-PRF under uplink-flexible mode.