Limits...
NLOS Correction/Exclusion for GNSS Measurement Using RAIM and City Building Models.

Hsu LT, Gu Y, Kamijo S - Sensors (Basel) (2015)

Bottom Line: The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange.Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal.According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

View Article: PubMed Central - PubMed

Affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. qmohsu@kmj.iis.u-tokyo.ac.jp.

ABSTRACT
Currently, global navigation satellite system (GNSS) receivers can provide accurate and reliable positioning service in open-field areas. However, their performance in the downtown areas of cities is still affected by the multipath and none-line-of-sight (NLOS) receptions. This paper proposes a new positioning method using 3D building models and the receiver autonomous integrity monitoring (RAIM) satellite selection method to achieve satisfactory positioning performance in urban area. The 3D building model uses a ray-tracing technique to simulate the line-of-sight (LOS) and NLOS signal travel distance, which is well-known as pseudorange, between the satellite and receiver. The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange. The measurement of the satellite will be excluded if the simulated and raw pseudoranges are inconsistent. Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal. According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

No MeSH data available.


Weighting of all the particles of point 272,697 before (a) and after RAIM (b).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4541937&req=5

sensors-15-17329-f013: Weighting of all the particles of point 272,697 before (a) and after RAIM (b).

Mentions: Figure 12 shows the dynamic pedestrian positioning results of the proposed 3D map method in the deep canyon. As can be seen in Figure 12, it is difficult to understand the trajectory of the pedestrian using the 3D map method (yellow dots). The 3D map method even gives a result with the wrong side of the street at many points. After applying the RAIM FDE, the positioning results of the 3D map method became much closer to the ground truth. Table 4 lists the lateral positioning performance of the conventional and 3D map methods. Both the conventional methods cannot provide accurate positioning service. It is interesting to note the WLS using only LOS has low availability because of the insufficient number of LOS satellites. Comparing the 3D map method before and after applying the RAIM FDE, there are about 4.9 and 2.1 m of improvements in terms of positioning mean error and standard deviation, respectively. Figure 12 shows that the positioning results before applying RAIM have about 12 m of lateral positioning error at point 272,748. After applying the RAIM, the positioning error is reduced to about 2 m. The improvements are due to the exclusion of the double reflected NLOS and strong multipath effects, as previous demonstrated in Figure 8 and Figure 10. The availability is also increased after applying the RAIM. Point 272,697 in Figure 12 is an example of the increase of the availability. The particle weighting distribution of the point 272,697 is shown in Figure 13.


NLOS Correction/Exclusion for GNSS Measurement Using RAIM and City Building Models.

Hsu LT, Gu Y, Kamijo S - Sensors (Basel) (2015)

Weighting of all the particles of point 272,697 before (a) and after RAIM (b).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541937&req=5

sensors-15-17329-f013: Weighting of all the particles of point 272,697 before (a) and after RAIM (b).
Mentions: Figure 12 shows the dynamic pedestrian positioning results of the proposed 3D map method in the deep canyon. As can be seen in Figure 12, it is difficult to understand the trajectory of the pedestrian using the 3D map method (yellow dots). The 3D map method even gives a result with the wrong side of the street at many points. After applying the RAIM FDE, the positioning results of the 3D map method became much closer to the ground truth. Table 4 lists the lateral positioning performance of the conventional and 3D map methods. Both the conventional methods cannot provide accurate positioning service. It is interesting to note the WLS using only LOS has low availability because of the insufficient number of LOS satellites. Comparing the 3D map method before and after applying the RAIM FDE, there are about 4.9 and 2.1 m of improvements in terms of positioning mean error and standard deviation, respectively. Figure 12 shows that the positioning results before applying RAIM have about 12 m of lateral positioning error at point 272,748. After applying the RAIM, the positioning error is reduced to about 2 m. The improvements are due to the exclusion of the double reflected NLOS and strong multipath effects, as previous demonstrated in Figure 8 and Figure 10. The availability is also increased after applying the RAIM. Point 272,697 in Figure 12 is an example of the increase of the availability. The particle weighting distribution of the point 272,697 is shown in Figure 13.

Bottom Line: The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange.Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal.According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

View Article: PubMed Central - PubMed

Affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan. qmohsu@kmj.iis.u-tokyo.ac.jp.

ABSTRACT
Currently, global navigation satellite system (GNSS) receivers can provide accurate and reliable positioning service in open-field areas. However, their performance in the downtown areas of cities is still affected by the multipath and none-line-of-sight (NLOS) receptions. This paper proposes a new positioning method using 3D building models and the receiver autonomous integrity monitoring (RAIM) satellite selection method to achieve satisfactory positioning performance in urban area. The 3D building model uses a ray-tracing technique to simulate the line-of-sight (LOS) and NLOS signal travel distance, which is well-known as pseudorange, between the satellite and receiver. The proposed RAIM fault detection and exclusion (FDE) is able to compare the similarity between the raw pseudorange measurement and the simulated pseudorange. The measurement of the satellite will be excluded if the simulated and raw pseudoranges are inconsistent. Because of the assumption of the single reflection in the ray-tracing technique, an inconsistent case indicates it is a double or multiple reflected NLOS signal. According to the experimental results, the RAIM satellite selection technique can reduce by about 8.4% and 36.2% the positioning solutions with large errors (solutions estimated on the wrong side of the road) for the 3D building model method in the middle and deep urban canyon environment, respectively.

No MeSH data available.