## 3 Results
### Experimental Results in Urban Canyon 1
#### 3.2.2 Positioning Results Comparison  
To validate the effectiveness of the adaptive GNSS-RTK/LIO fusion method for continuous position estimation, the trajectories generated by the adaptive integrated pipelines with thresholds \(el_{th}\) for the GNSS-RTK availability assessment equals 90\({}^{\circ}\), 35\({}^{\circ}\), and 15\({}^{\circ}\) are presented respectively in Figure 7a-c. All the u-blox RTK solutions processed by RTK-LIB [7], among which no fixed ones were reported, with a mean elevation angle mask smaller than \(el_{th}\) are fused with LiDAR and IMU measurements as Equation (11). When \(el_{th}\) equals 90\({}^{\circ}\), as the mean elevation angle mask must be smaller than 90\({}^{\circ}\), all the developed u-blox RTK solutions are integrated. Unavailable solutions with large errors would destroy the estimation, while the smaller \(el_{th}\) rejects more unavailable ones, and therefore make more accurate position estimation. As shown in Figure 7a-c, the smaller \(el_{th}\) is, the better its corresponding trajectory overlaps with the ground truth. The box plot in Figure 7d further shows the precision of the three trajectories quantitatively.  
Table 3 shows the precision of the positioning results from alone GNSS-RTK measurements, the LIO, the LIO-SAM [42], and the three adaptive integrated pipelines quantitatively. The ATE of the pure GNSS-RTK is quite large with an RMSE of 42.02 m. The LIO achieves the best precision with the RMSE of 3.99 m as marked in bold font. The RMSE of ATE of the position estimated by the traditional fusion method LIO-SAM [42] is about 19.89 m. Among the adaptive integrated GNSS-RTK/LIO methods, when \(el_{th}\) equals 90\({}^{\circ}\), the RMSE of ATE is 25.33 m. In LIO-SAM [42], only when the covariance of the pose generated by LIO exceeds a preset threshold, which means the reliability of the LIO decreases, the GNSS-RTK solutions without assessment are included for state optimization and correction. The proposed fusion pipeline with \(el_{th}\) equals 90\({}^{\circ}\) fused all the received  
Figure 7: (**a–c**), plots the trajectory generated by pipelines with the thresholds \(el_{th}\) for the GNSS-RTK availability assessment set as 90\({}^{\circ}\), 35\({}^{\circ}\), and 15\({}^{\circ}\) respectively on urban-1. The black trajectory is the ground truth. The ATE of each estimated position is mapped on the trajectory referring to the color bar with the same scale on the right, on which the largest and the smallest tick label represent the maximum and the minimum ATE respectively while the middle one represents the midrange of them. (**d**) shows the boxplot of the ATE on the whole trajectory produced by the pipelines with three different thresholds.  
GNSS-RTK solutions which would be more than that used in LIO-SAM [42]. Considering that the GNSS-RTK solution on this data has a large error, the positioning accuracy of the proposed pipeline with \(el_{th}\) equals 90\({}^{\circ}\) is lower than that of LIO-SAM [42] consequently. By decreasing the \(el_{th}\) to 35\({}^{\circ}\), a 25% improved RMSE of 18.88 m is achieved. With \(el_{th}\) set to 15\({}^{\circ}\) the next best precision is obtained.