GNSS Receiver Convergence Selection via Movement Sensor Threshold
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Solution Overview
Problem
GNSS receivers experience prolonged convergence times when restarted after being moved from their previous location, as they rely on a short convergence algorithm that leads to errors, taking significantly longer than a cold-start convergence process.
Innovation Solution
A system that determines the net movement of the GNSS antenna using movement sensors and selects between a short or long convergence algorithm based on the threshold net movement parameter, ensuring accurate and efficient re-convergence by initiating the appropriate algorithm upon startup.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a previously converged GNSS receiver uses its previous known position for convergence upon start-up, then convergence time is shortened to a few minutes or less, but if the receiver has been moved after shut-down, this results in prolonged convergence time exceeding 30 minutes
Solution Approach 1:
The system performs preliminary monitoring of movement sensor data during the shut-down period to detect whether the antenna has been moved. This advance detection allows the system to prepare and select the appropriate convergence algorithm before the convergence process begins, preventing the problem of using an inappropriate algorithm that would lead to prolonged convergence time.
Solution Approach 2:
The system dynamically adjusts the convergence algorithm selection based on the detected movement condition. Instead of using a fixed convergence approach, the system transitions between different convergence modes (fast convergence when no movement detected, standard convergence when movement detected) based on real-time sensor data, optimizing both speed and accuracy.
2Reliability
If a GNSS receiver performs a cold-start convergence process, then convergence accuracy is maintained, but convergence time increases to approximately 30 minutes or more
Solution Approach 1:
The system applies different convergence algorithms to different local conditions (movement vs. no movement). Instead of using a uniform convergence approach for all situations, the system tailors the convergence method to the specific condition detected by the movement sensor, applying fast convergence when appropriate and standard convergence when needed.
Solution Approach 2:
The system changes the convergence parameter (algorithm selection) based on the detected movement condition. By monitoring movement sensor data and adjusting the convergence algorithm accordingly, the system optimizes the balance between convergence speed and accuracy for each specific situation.
3Speed
If a GNSS receiver attempts to use a fast convergence algorithm after movement has occurred, then convergence speed is maintained, but convergence accuracy deteriorates leading to errors
Solution Approach 1:
The system uses movement sensor data as feedback to determine whether the antenna has been moved. This feedback mechanism allows the system to detect the movement condition and adjust the convergence algorithm selection accordingly, preventing the use of fast convergence when it would lead to errors while maintaining its speed benefits when appropriate.
Data Source
AI summary
A method of implementing convergence selection of a Global Navigation Satellite System (GNSS) receiver is disclosed. In accordance with one embodiment, a GNSS receiver which is coupled with a mobile machine is shut down. The GNSS receiver is in a converged state at shut down. A movement sensor is monitored to determine if net movement of a GNSS antenna coupled with the mobile machine exceeds a threshold net movement parameter while the GNSS receiver is shut down. Upon power up of the GNSS receiver, a shorter convergence algorithm is initiated in response to determining that the threshold net movement parameter has not been exceeded and a longer convergence algorithm is initiated in response to determining that the threshold net movement parameter has been exceeded.