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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.


Histogram of the lateral positioning error of the proposed 3D map method before and after using the RAIM satellite selection method in the deep urban canyon.
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sensors-15-17329-f016: Histogram of the lateral positioning error of the proposed 3D map method before and after using the RAIM satellite selection method in the deep urban canyon.

Mentions: This subsection focuses on the statistical comparison of the proposed 3D map method before and after using the RAIM satellite selection technique. The GNSS positioning solution is large in lateral direction, especially in urban canyon environments. It is essential to study the histogram of the lateral positioning error. This paper defines the bins of the histogram as the percentage of the road width, as shown in Figure 14. The experiments are conducted in both middle and deep urban canyon. The road widths of the experimental place are about 20 m. As can be seen, if the lateral positioning error is larger than 50% of the road width, namely larger than 10 m, the pedestrian is estimated on the wrong side of the road. The point with positioning error less than 3 m are classified as accurate solutions. In this experiment, the pedestrian walks the street back and forth. The trajectory is as the red line in Figure 14. The lengths of the data used are about 20 min, which contains about 1200 epochs. The results in the middle and deep urban canyon are shown in Figure 15 and Figure 16, respectively. In Figure 15, about 16.7% of the estimated positions are located on the wrong side of the road before using the proposed RAIM. With the adding of RAIM, it is reduced to only 8.3%. Note that the most of the 8.4% reduction of the point with larger error are corrected to about 4 and 5 m. Note that the RAIM method can improve the proposed 3D map only in the case of receiving the multiple NLOS reflections or the abnormal measurements. As a result, positioning solutions with less than 3 m positioning error both before and after using RAIM are very similar, which account for 53.8% and 58.4% of solutions, respectively. In the case of the deep urban canyon, almost half of the solutions estimated by the 3D map method are on the wrong side of the street, as shown in Figure 16. This can be reduced to 13.7% if the RAIM satellite selection is applied. The positioning solutions within a level of 3 m lateral positioning error both before and after using RAIM are 10.2% and 61.5%, respectively. This result shows the RAIM FDE is essential for the proposed 3D map positioning method, especially in the deep urban canyon environment.


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

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

Histogram of the lateral positioning error of the proposed 3D map method before and after using the RAIM satellite selection method in the deep urban canyon.
© Copyright Policy
Related In: Results  -  Collection

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

sensors-15-17329-f016: Histogram of the lateral positioning error of the proposed 3D map method before and after using the RAIM satellite selection method in the deep urban canyon.
Mentions: This subsection focuses on the statistical comparison of the proposed 3D map method before and after using the RAIM satellite selection technique. The GNSS positioning solution is large in lateral direction, especially in urban canyon environments. It is essential to study the histogram of the lateral positioning error. This paper defines the bins of the histogram as the percentage of the road width, as shown in Figure 14. The experiments are conducted in both middle and deep urban canyon. The road widths of the experimental place are about 20 m. As can be seen, if the lateral positioning error is larger than 50% of the road width, namely larger than 10 m, the pedestrian is estimated on the wrong side of the road. The point with positioning error less than 3 m are classified as accurate solutions. In this experiment, the pedestrian walks the street back and forth. The trajectory is as the red line in Figure 14. The lengths of the data used are about 20 min, which contains about 1200 epochs. The results in the middle and deep urban canyon are shown in Figure 15 and Figure 16, respectively. In Figure 15, about 16.7% of the estimated positions are located on the wrong side of the road before using the proposed RAIM. With the adding of RAIM, it is reduced to only 8.3%. Note that the most of the 8.4% reduction of the point with larger error are corrected to about 4 and 5 m. Note that the RAIM method can improve the proposed 3D map only in the case of receiving the multiple NLOS reflections or the abnormal measurements. As a result, positioning solutions with less than 3 m positioning error both before and after using RAIM are very similar, which account for 53.8% and 58.4% of solutions, respectively. In the case of the deep urban canyon, almost half of the solutions estimated by the 3D map method are on the wrong side of the street, as shown in Figure 16. This can be reduced to 13.7% if the RAIM satellite selection is applied. The positioning solutions within a level of 3 m lateral positioning error both before and after using RAIM are 10.2% and 61.5%, respectively. This result shows the RAIM FDE is essential for the proposed 3D map positioning method, especially in the deep urban canyon environment.

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.