Dynamic RTK Reference Stations Using Autonomous Vehicles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The traditional RTK positioning technique has a limited effective action distance due to the linear attenuation of GPS error correlation with distance, resulting in reduced accuracy and non-computability of carrier phase ambiguity, and requires numerous costly static reference stations and dedicated user terminals.
Innovation Solution
Autonomous driving cars are used as dynamic reference stations to provide RTK position correction data to a network server, which fuses data from multiple cars to offer high accuracy positioning, expanding the service area and reducing costs by replacing static stations and eliminating the need for dedicated terminals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional static RTK reference stations are used, then positioning accuracy is maintained within limited range, but system cost increases and service area is restricted
Solution Approach 1:
The patent transforms static reference stations into dynamic mobile reference stations using autonomous driving cars. These vehicles continuously move and transmit positioning data, enabling the system to cover expanding geographic areas while maintaining RTK-level accuracy through real-time data transmission to cloud servers.
Solution Approach 2:
The mobile reference stations serve multiple functions: they act as positioning references for RTK correction, collect road condition data, and provide navigation information. This multi-functionality reduces the need for dedicated infrastructure while expanding service coverage.
2Measurement precision
If traditional static RTK reference stations are deployed, then positioning accuracy is ensured, but system cost increases due to numerous required stations
Solution Approach 1:
Autonomous driving cars equipped with positioning systems serve as their own reference stations, eliminating the need for dedicated static infrastructure. The vehicles' existing navigation and sensing systems are repurposed to provide RTK correction data, reducing overall system cost.
Solution Approach 2:
The system changes the operational parameters of reference stations from static to mobile, allowing a smaller number of vehicles to cover larger areas through movement, thereby reducing the total quantity of reference stations needed while maintaining accuracy.
3Measurement precision
If dedicated RTK GPS receiver terminals are used, then high accuracy positioning is achieved, but device complexity and cost increase
Solution Approach 1:
The patent introduces a cloud server as an intermediary that processes RTK correction data and delivers it to standard mobile devices. This mediator enables high-accuracy positioning without requiring specialized RTK hardware in end-user devices, reducing complexity while maintaining precision.
Solution Approach 2:
The system transfers the complex RTK processing functionality from end-user devices to centralized cloud servers. Standard mobile devices receive simplified correction data through apps, eliminating the need for dedicated RTK receivers while achieving the same positioning accuracy.
Data Source
AI summary
A positioning system including an autonomous driving car used as a dynamic reference station to provide data required for Real-Time Kinematic (RTK) position correction; and a network server for receiving the data from the autonomous driving car to provide RTK position correction data to an end user. Further, a positioning method realized by this system is provided. This positioning system and methods are capable of considerably expanding the service range and significantly reducing the cost by utilizing an autonomous driving (AD) car for providing the data required for position correction.