Reliable GNSS positioning and navigation with simultaneous multipath and NLOS mitigation by using camera and C/N0 at deep canyons

Abstract Global navigation satellite system (GNSS) is one of the primary technologies providing global positioning services for various location-based applications. However, the accuracy and availability of GNSS positioning and navigation at deep canyons are unsatisfactory. This paper proposes an improved vision-aided GNSS positioning and navigation method to detect the GNSS multipath and non-line-of-sight (NLOS) signals simultaneously and correct them at deep canyons. Specifically, the sky-pointing fisheye camera is employed to detect the positions and spatial distribution of satellites relative to the receiver. The sky and nonsky areas are segmented, and satellites are projected onto the segmented images based on their azimuth and elevation, classifying the satellites into NLOS, LOS, and multipath signals simultaneously. Then considering inaccuracies in obstruction assessment and camera distortion, an improved weighting strategy is employed to address these three types of errors. An adaptive three-segment elevation-C/N0 model containing the C/N0 factors is deduced to process further and differentiate these signals. To evaluate the performance of the proposed improved vision-aided GNSS method, a measurement campaign was conducted. Compared to the GNSS and traditional vision-aided GNSS methods, the root mean squared errors of the proposed method in three directions are all smaller than 10 m, and achieve accuracy improvements of 41.20% and 40.28%, respectively. Therefore, the proposed method is more precise and reliable, especially at deep canyons.