## 4 Flight Experiment Results
The time synchronization performance is an important measure to operate a ground-based radio navigation system within a specific accuracy level  
Figure 12: The unmanned helicopter and navigation sensor used for the flight tests. in real time. In this study, all of the ground sensors used multiple correlators in the code-tracking loop to reduce the multipath errors from inland areas. However, a simple narrow correlator was implemented in the user sensor installed in the unmanned helicopter to reduce the possibility of a loss of lock during the flight. Figure 13 depicts a computed version of the horizontal DOP of the flight test area. The master station is centered on four slave stations optimally placed in the test area. The DOP has a minimum value close to the master station, which is located at the center of Figure 13, and this value increases exponentially if a user vehicle moves away from the center. The trajectory of the unmanned vehicle equipped with the DUT (device under test) was scheduled to cross the center area to ascertain the condition that led to the best performance. In this paper, we assumed a horizontal DOP (HDOP) of two or less as the operational criteria to define the effective mission area of the vehicle. The real-time flight trajectories using the GRNS signals, as well as the post-processed CDGPS results using GNSS signals are shown in Figure 14 together. Position calculation in the developed sensor was done, and the results were stored at 10 Hz. In the unmanned helicopter, a NovAtel GNSS receiver was equipped to store the log files. The precise positions of the vehicle were computed to mm to cm accuracy by the GrafNav software. To provide correction information to the program, a DGPS reference station was installed very close to the master station with a NovAtel OEM6 receiver. We had conducted flight tests several times with UAV helicopters; however, from Figure 14 to Figure 16, we focused on the first flight result to explain the flight analysis clearly. In Figure 14, we present a 2D trajectory of the first flight in ENU (east-north-up) coordinates. Figure 14a shows a full trajectory, and Figure 14b presents a zoomed-in trajectory of the right upper corner of Figure 14a to show the positioning error in detail. Very large outliers were noted, as marked with the blue dots in Figure 14a. Poor condition numbers in the least squares estimator caused the outliers, which occurred during a low-elevation stage. When the altitude of the flight vehicle is low, the navigation sensor attached to the vehicle experiences low visibility due to the geometrical environment,  
Figure 13: Horizontal dilution of precision (HDOP) of the test area. unstable signal power conditions and the poor DOP situation. The last factor is the most critical error source related to the outliers. The trajectory shown with the black circle only close to the upper left corner does not have a three-dimensional navigation solution due to a visibility problem (_i.e.,_ the low elevation). The upper right corner of Figure 14a corresponds to the best DOP area, which is above the area of the master station. At every corner of the trajectory, the unmanned helicopter stayed for some minutes in hovering mode and changed its heading to an appropriate direction. Just after the rotation of the head, the navigation sensor experienced positioning errors distributed in a specific direction, as can be seen in the corner area of the zoomed-in Figure 14b. We suspect that blockages by the leg structures of the unmanned helicopter and the gain patterns of the equipped antennas likely caused these errors during the rotation. Because we applied the spatial diversity combining technique to the stations installed on the ground and to the navigation sensor equipped on the vehicle, the performance degradation due to rotation must be minimized.