Science

From the road to the cloud: Leveraging vehicle Global Navigation Satellite System raw data

Crowdsourcing RTK: a brand new GNSS positioning framework for constructing spatial high-resolution atmospheric maps primarily based on huge car GNSS knowledge. Credit: Satellite tv for pc Navigation (2024). DOI: 10.1186/s43020-024-00135-8

Revolutionary International Navigation Satellite tv for pc System (GNSS) positioning applied sciences harness huge vehicle-generated knowledge to create high-resolution atmospheric delay correction maps, considerably enhancing International Positioning System (GPS) accuracy throughout diversified spatial scales. This new methodology exploits real-time, crowd-sourced car GNSS uncooked knowledge, refining conventional GPS functions and presenting a cheap answer for exact positioning.

The hunt for enhanced International Navigation Satellite tv for pc System (GNSS) accuracy has been hindered by the constraints of present atmospheric correction fashions, which rely upon sparse, high-cost infrastructure. These conventional fashions battle to offer the high-resolution knowledge obligatory for exact positioning, particularly in dynamic environments like autonomous driving. The arrival of this research addresses this problem by proposing a crowdsourced strategy to generate detailed atmospheric maps, promising to considerably enhance GNSS efficiency and scale back prices.

Researchers from the Chinese language Academy of Sciences have developed an revolutionary GNSS positioning framework published on May 13 2024, in Satellite tv for pc Navigation. The research particulars a system that makes use of twin base stations and Crowdsourced Atmospheric delay correction Maps (CAM) to realize high-precision positioning, a big development for functions similar to autonomous driving and Web of Issues (IoT).

The analysis introduces a novel GNSS positioning framework that leverages twin base stations and big vehicle knowledge to supply high-resolution atmospheric maps, enhancing the precision of GNSS. This crowd-sourced strategy, termed CAM, makes use of knowledge from autos outfitted with GNSS receivers.

These autos gather and transmit atmospheric delay knowledge to a cloud server the place it’s built-in and processed to repeatedly replace the CAM. This dynamic updating course of improves each the CAM spatial decision and the positioning accuracy for public customers in real-time. The core innovation of this framework lies in its use of frequent car GNSS knowledge, which is extra ample and available in comparison with conventional knowledge sources.

By aggregating and refining this knowledge, the research achieves a cheap methodology for producing detailed atmospheric delay corrections. The CAM considerably reduces the reliance on costly and fewer distributed Steady Operational Reference System (CORS) stations historically used for atmospheric knowledge, providing a scalable answer that enhances the feasibility and accuracy of precision GNSS functions.

Dr. Yunbin Yuan, lead researcher, states, “This framework not only lowers the costs of atmospheric data collection but also significantly increases the accuracy and reliability of GNSS positioning, marking a significant leap forward in location-based services.”

The appliance of this expertise extends past improved International Positioning System (GPS) accuracy; it additionally opens avenues for real-time environmental monitoring and has important implications for urban planning, transportation, and emergency response techniques. As autos grow to be knowledge assortment hubs, the scalability of this expertise guarantees intensive socio-economic advantages, significantly in extremely urbanized areas.

Extra info:
Hongjin Xu et al, Crowdsourcing RTK: a brand new GNSS positioning framework for constructing spatial high-resolution atmospheric maps primarily based on huge car GNSS knowledge, Satellite tv for pc Navigation (2024). DOI: 10.1186/s43020-024-00135-8

Supplied by
Aerospace Data Research Institute, Chinese language Academy of Sciences

Quotation:
From the street to the cloud: Leveraging car International Navigation Satellite tv for pc System uncooked knowledge (2024, May 17)
retrieved 17 May 2024
from https://techxplore.com/information/2024-05-road-cloud-leveraging-vehicle-global.html

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