Improved Navigation Based on Received Signal Quality Monitoring (RSQM)

The global navigation satellite system (GNSS) provides an easy, efficient, and cost-effective way to determine position, time, and direction anywhere around the globe. However, standard GNSS can provide users with highly accurate positioning information in clear open sky environments only and often lacks consistency in maintaining required navigation performance thresholds in the urbanized environments. In such operating environments, the quality of GNSS signals is significantly degraded due to multipath (MP) and non-line-of-sight (NLOS) reception which can ultimately result in inaccurate estimation of position and navigation parameters. The MP/NLOS reception remains a potential obstacle to the practical realization of GNSS in highly urbanized environments, and the severity of the effect varies greatly with the type of environment. Thus, in order to meet stringent requirements defined for practical applications of GNSS, the characterization of signal disruption which could significantly affect a GNSS performance is highly important. In this paper, an adaptive signal quality monitoring (RSQM) method is proposed which can monitor the quality of signal and anticipate the possible degradation by investigating the temporal variations in GNSS features. The proposed RSQM method performs rigorous quality tests on GNSS fundamental features, i.e., carrier-to-noise ratio (CNR) and range residuals, and then ranks the quality of signal into three categories, i.e., best, mediocre, and worse. Leveraging the redundancy of range measurements, the RSQM selects navigation signals having the best quality and discards or de-weights the poor quality signals. To validate the performance of the proposed RSQM algorithm, a detailed study on the performance of a multi-GNSS receiver in the quad-constellation mode has been carried out on a pre-surveyed track. The experimental results show that RSQM method can accurately detect and categorize the signal quality which can help in improving the navigation accuracy by suppressing the MP/NLOS effects.