Parallel Processing for Fast Integer Bias Estimation in Positioning Systems
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Solution Overview
Problem
Current positioning systems face challenges in efficiently estimating integer value bias at high speeds, particularly in RTK methods where multiple calculation processing items require significant time and resources.
Innovation Solution
The proposed positioning system performs interference positioning by executing multiple calculation processing items in parallel with different start time points, utilizing parallel processing and periodic updates of positioning data to optimize the estimation of integer value bias, thereby reducing calculation time and resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple calculation processing items are performed sequentially to ensure accurate integer value bias estimation, then measurement precision is improved, but productivity deteriorates due to increased calculation time
Solution Approach 1:
The positioning system divides the calculation processing into multiple independent calculation processing items, each handling different time points as start points. These segmented calculations are then executed in parallel rather than sequentially, allowing the system to maintain high precision through multiple processing paths while improving productivity through concurrent execution.
Solution Approach 2:
The system transitions from one-dimensional sequential processing to multi-dimensional parallel processing by introducing the time dimension as a parallelization axis. Multiple calculation processing items operate simultaneously at different time points, effectively adding a temporal dimension to the processing architecture that enables both high precision and fast positioning.
2Productivity
If multiple calculation processing items are performed in parallel to improve positioning speed, then productivity is improved, but device complexity worsens due to increased processing requirements
Solution Approach 1:
By segmenting the calculation into independent processing items that can be executed in parallel, the system distributes the computational load across multiple tasks. Each segment handles a specific time point's calculations, reducing the complexity burden on any single processing unit while collectively achieving high-speed positioning through parallel execution.
3Use of energy by moving object
If sequential processing is used to reduce computational resources, then use of energy is reduced, but loss of time increases due to slower processing
Solution Approach 1:
The positioning system employs periodic action by performing multiple calculation processing items at different periodic time points in parallel. This approach optimizes energy usage by distributing computational tasks across time periods rather than concentrating them, while simultaneously reducing total processing time through concurrent execution of these periodic calculations.
Data Source
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AI summary
The present disclosure is effective in easily estimating an integer value bias at a high speed. A processor of a positioning system, a positioning method, a positioning station in the present disclosure performs interference positioning through calculation processing based on positioning data of the base station and positioning data of the positioning station. A plurality of calculation processing items are performed in parallel with different time points as start time points. In this way, even in a case where a situation in which the time required for the calculation of a fix solution differs depending on time point at which time point the calculation processing starts, there is a possibility that one of a plurality of calculation processing items can calculate the fix solution at an earlier time than in a case where single calculation processing performs the calculation. Therefore, it is possible to easily estimate the integer value bias at the high speed.