Terminal Positioning via Wireless Eigenvalue Interpolation
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Solution Overview
Problem
The existing RFPM positioning technology faces challenges in achieving accurate terminal location positioning due to the need for extensive preliminary measurements, which increases workload and resource consumption without necessarily improving accuracy.
Innovation Solution
A method and device that calculate location information of an estimated point using a set algorithm based on an original point's information, and then use the calculated wireless eigenvalue of the estimated point to position the terminal, allowing for improved accuracy without increasing measurement workload by fitting location information and wireless eigenvalues of unmeasured raster points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the area occupied by one raster is made relatively small to improve positioning accuracy, then positioning accuracy is improved, but measurement workload is additionally increased
Solution Approach 1:
The patent divides the measurement process into two segments: (1) coarse measurement phase where only original points are measured, and (2) fine estimation phase where estimated points are calculated using interpolation algorithms. This segmentation allows the system to achieve high positioning accuracy through calculated estimated points without proportionally increasing actual measurement workload, as the estimation process replaces extensive fine-grained measurements.
Solution Approach 2:
The patent performs preliminary measurements only at original points before generating estimated points through calculation. By conducting measurements in advance at a coarse granularity and then using algorithms to estimate values at finer granularity points, the system prepares sufficient data for accurate positioning without undertaking the full measurement workload that would be required if all fine-granularity points were measured directly.
2Measurement precision
If extensive preliminary measurements are performed to improve positioning accuracy, then positioning accuracy is improved, but resource consumption increases
Solution Approach 1:
The patent creates copies of measurement data through calculated estimated points that replicate the characteristics of actual measurements without requiring physical measurement resources. The estimation algorithms generate virtual measurement data at estimated points by interpolating from original point measurements, thereby achieving comprehensive coverage with minimal actual resource consumption.
3Measurement precision
If the division granularity of raster measurements is refined to improve positioning accuracy, then positioning accuracy is improved, but measurement workload increases
Solution Approach 1:
The patent segments the raster division into original points (coarse grid) and estimated points (fine grid). The coarse original points are sparsely measured, while the fine estimated points are generated through interpolation calculations. This segmentation enables refined division granularity for accurate positioning without proportionally increasing measurement workload, as the fine-granularity points are computed rather than measured.
Solution Approach 2:
The patent introduces estimation algorithms as intermediaries between original point measurements and final positioning results. These algorithms act as mediators that translate sparse original point data into comprehensive estimated point data, enabling fine-granularity positioning accuracy without requiring fine-granularity measurements, thus reducing measurement workload while maintaining refined division granularity.
Data Source
AI summary
The present invention discloses a method, which mainly includes: calculating location information of a estimated point by using a set algorithm according to location information of an original point; and calculating a wireless eigenvalue of the estimated point according to a wireless eigenvalue of the original point obtained by measuring; when a wireless eigenvalue reported by a terminal is received, positioning a location of the terminal according to the wireless eigenvalue of the original point and the wireless eigenvalue of the estimated point. In this way, in a mathematical model manner, location information and a wireless eigenvalue of an unmeasured raster point are fitted, with no need to increase an additional measurement workload, thereby saving a resource. In addition, a division granularity of raster measurement may be changed according to an actual requirement, thereby improving accuracy of terminal positioning.