GNSS augmentation

About: GNSS augmentation is a research topic. Over the lifetime, 2478 publications have been published within this topic receiving 28513 citations. The topic is also known as: SBAS & Satellite Based Augmentation System.

Improving Localization Accuracy in Connected Vehicle Networks Using Rao–Blackwellized Particle Filters: Theory, Simulations, and Experiments

Abstract: A crucial function for automated vehicle technologies is accurate localization. Lane-level accuracy is not readily available from low-cost global navigation satellite system (GNSS) receivers because of factors such as multipath error and atmospheric bias. Approaches such as differential GNSS can improve localization accuracy, but usually require investment in expensive base stations. Connected vehicle technologies provide an alternative approach in improving the localization accuracy. It will be shown in this paper that localization accuracy can be enhanced using crude GNSS measurements from a group of connected vehicles, by matching their locations to a digital map. A Rao–Blackwellized particle filter is used to jointly estimate the common biases of the pseudo-ranges and the vehicle positions. Multipath biases, which introduce receiver-specific (non-common) error, are mitigated by a multi-hypothesis detection-rejection approach. The temporal correlation of the estimations is exploited through the prediction-update process. The proposed approach is compared with existing methods using both simulations and experimental results. It was found that the proposed algorithm can eliminate the common biases and reduce the localization error to below 1 m under open sky conditions.

GNSS Accuracy Improvement Using Rapid Shadow Transitions

Abstract: Receiver modules in Global Navigation Satellite Systems (GNSS) are capable of providing positioning and velocity estimations that are sufficiently accurate for the purpose of road navigation. However, even in optimal open-sky conditions, GNSS-based positioning carries an average error of 2–4 m. This imposes an effective limitation on GNSS-based vehicle lane detection, a desired functionality for various navigation and safety applications. In this paper, we present a novel framework for lane-level accuracy using GNSS devices and 3-D shadow matching. The suggested framework is based on detection and analysis of rapid changes in navigation satellites' signal strength, which are caused by momentary blockages due to utility and light poles. A method for detecting such momentary changes between line of sight and non line of sight is presented, followed by a geometric algorithm that improves location accuracy of commercial GNSS devices. We have tested the framework's applicability using both simulations and field experiments. We provide the results of these tests and discuss receiver-side sampling rate requirements for high-performance lane-level positioning.

Satellite radar interferometry: Potential and limitations for structural assessment and monitoring

Abstract: The present paper analyzes potential and limitations of multi-temporal Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques applied for the structural monitoring and assessment of constructions affected by different external actions. A comprehensive approach for the processing, interpretation and proper use of satellite radar interferometry data for structural analyses at urban and single-construction scales is proposed. Following a brief literature review, highlighting the most relevant applications in this field, some aspects concerning DInSAR techniques are shortly summarized, particularly focusing on the Small BAseline Subset (SBAS) approach applied to perform advanced analyses at structural level. Then, the main issues of the DInSAR measurements exploitation for structural applications are discussed, focusing on the use of both one or two datasets relevant to ascending and descending satellite passes. Analysis at the scale of single construction (i.e., building, bridge, etc.) of displacements time series and mean deformation velocities is discussed, in order to identify scenarios that may become potentially critical for the structures. Some application examples are provided, employing COSMO-SkyMed (CSK) datasets relative to the urban area of Rome (Italy), acquired during the 2011–2019 time interval and processed through the SBAS algorithm. Specific considerations related to the use of DInSAR measurements for structural monitoring and assessment are then proposed, also discussing possible approaches for preliminary and detailed evaluation of structural damages.

Estimating and predicting structures proximate to a mobile device

Abstract: The description relates to mobile device location. One example can identify global navigation satellite system (GNSS) satellites expected to be in line-of-sight of a mobile device. This example can detect differences between received GNSS data signals and expected GNSS data signals from the expected GNSS satellites. The example can also determine a direction from the mobile device of an obstruction that is causing at least some of the detected differences.