# An RTK UAV-Based Method for Radial Velocity Validation of Weather Radar
## 4 Results
### Comparative Analysis of Radar-Measured Radial Velocity  
When the UAV is hovering, the radar-measured velocity should theoretically be 0 m/s. However, the attitude of the UAV is influenced by factors such as wind speed and the rotor, which could alter velocity components along the radar radial direction, affecting the measurement results. Therefore, the experiment first compared the velocity accuracy in the hovering state of the UAV and then analyzed the measurement instability introduced by the attitude of the UAV. As shown in Figure 13, when the UAV velocity varies by less than 0.2 m/s, the corresponding intensity values also show small variations, and the target RCS remains relatively constant. However, if the UAV velocity varies significantly (as highlighted by the red box in the figure below), there is a difference of approximately 10 dB in the intensity of the target. The standard deviation of the measured radial velocity is 0.135, with a mean value of \(-0.069\) m/s, according to the complete recorded data in the hovering state. Therefore, the more stable the UAV state, the higher the quality of the corresponding velocity measurement. Conversely, if the UAV RCS varies significantly, the influence of the UAV attitude on the radar measurement results will be more evident. This further validates the correlation between target velocity and intensity in the radar signal processing algorithm. Figure 12: Radar monitoring and analysis of the velocity state of the UAV. (**a**) The whole process; (**b**) hover; (**c**) 7 m/s; (**d**) \(-\)10 m/s; (**e**) 8 m/s; (**f**) \(-\)10 m/s. Figure 13: The UAV-measured velocity while hovering. According to the UAV intensity and velocity rule observed during the hovering state, we developed a valid data-filtering method based on non-zero velocity using the target intensity. First, three contiguous range bins were selected for each route. Then, within each range bin, five pairs of data were selected with continuous stable values near the maxima that did not vary by more than 1 dB. These selected data were considered the effective measured data for radial velocity comparison. At the same time, taking into consideration the random jitter in the UAV velocity, data periods with relatively stable UAV velocities were selected during the comparison to ensure the reliability of the velocity reference values. Based on stable and effective comparison data pairs, the minimum absolute deviation between the UAV velocity reference values and the radar-measured values was used as the optimal absolute accuracy for the radial velocity validation. By calculating the standard deviation of the actual measured velocities on the same route, the relative accuracy of the weather radar velocity validation was assessed. The scientific validity of the validation method proposed in this study and the rationality of optimizing the evaluation indicators were analyzed using radar-measured data. We analyze the data in detail in Table 7. Analyzed from a quantitative point of view, the maximum deviation at +7 m/s was 0.04 m/s and the minimum deviation was 0.02 m/s; the maximum deviation at +8 m/s was 0.22 m/s and the minimum deviation was 0.04 m/s. This is because when the UAV is working at lower velocities, the reference velocity variations are minimal, resulting in a larger continuous and stable data period. This increases the reliability of the reference values during synchronous comparisons. Conversely, at a velocity of \(-\)10 m/s, the minimum deviation was no greater than 0.05 m/s, and the maximum deviation approached 0.5 m/s. This is attributed to the inadequate stability of the UAV internal state at high velocities, resulting in abrupt changes in adjacent velocity reference values of approximately \(\pm\)0.5 m/s. Moreover, the maximum deviation could potentially include a systemic bias associated with velocity discontinuity.