Abstract:
Accurate and reliable positioning of road vehicles is of great significance in several location-aware applications of cooperative intelligent transport systems, especiall...Show MoreMetadata
Abstract:
Accurate and reliable positioning of road vehicles is of great significance in several location-aware applications of cooperative intelligent transport systems, especially applications by means of the Global Navigation Satellite Systems (GNSSs). However, the performance of GNSS-based vehicle positioning is degraded under challenged signal observing environments. Due to the difficulties in GNSS observation quality modeling in the urban areas, the data-driven modeling provides an alternative approach to assist the GNSS integrity monitoring, which makes it possible to ensure the trustiness and safety in certain critical applications. In this paper, according to the concept of “local integrity”, a GNSS observation quality modeling method using GNSS pseudorange residual data within different time slots is presented, and the derived local models are employed to adjust the weights of satellite measurements in navigation calculation. The residual-based Receiver Autonomous Integrity Monitoring (RAIM) algorithm is improved by using local GNSS observation quality models under a Weighted Least Squares (WLS) frame. Results from field experiment validate the capability of the local weighting approach in enhancing integrity monitoring against the fault conditions of GNSS measurements.
Date of Conference: 04-07 November 2018
Date Added to IEEE Xplore: 09 December 2018
ISBN Information: