Position Estimation Device Using Coordinate-Axial Prioritization
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Solution Overview
Problem
Conventional position estimation techniques face challenges in achieving high accuracy when statistical data of multipath components cannot be collected in advance, or when the accuracy of such data is low.
Innovation Solution
A position estimation device that calculates the coordinate-axial position of a mobile station based on distance measurement results from multiple fixed stations, using a method that prioritizes the coordinate axis with the largest distance between fixed stations, thereby reducing estimation errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistical data of multipath components is collected in advance for each area, then position estimation accuracy is improved, but device complexity and data collection requirements increase
Solution Approach 1:
The system performs self-calibration by automatically collecting multipath component statistics during normal operation and storing them locally in the position estimation device, eliminating the need for external data collection systems or manual preprocessing. The device serves itself by gathering and utilizing its own operational data for accuracy improvement.
Solution Approach 2:
The system collects and stores statistical data of multipath components in advance during periods when position estimation is not critically needed or during idle time slots. This preliminary data collection enables the system to have accurate statistical information ready before it is actually needed for high-precision position estimation, resolving the contradiction between having accurate data and system complexity.
2Measurement precision
If sequential approximate calculation is used to solve three-dimensional nonlinear simultaneous equations, then position estimation is achieved, but calculation time and processing complexity increase
Solution Approach 1:
The three-dimensional nonlinear simultaneous equations are segmented into multiple one-dimensional linear equations by sequentially solving for each coordinate axis independently. This segmentation transforms a complex three-dimensional problem into simpler one-dimensional problems that can be solved faster using least squares method, reducing overall calculation time while maintaining accuracy.
Solution Approach 2:
The system dynamically adjusts the calculation approach by first attempting the faster segmented least squares method, and only resorting to sequential approximate calculation when higher precision is required or when the segmented method converges insufficiently. This dynamic adaptation optimizes calculation time while maintaining necessary accuracy.
3Measurement precision
If distance measurement results from all fixed stations are used equally in position estimation, then simplicity is maintained, but accuracy decreases when some measurements are affected by multipath components
Solution Approach 1:
Different weight coefficients are assigned to different distance measurement results based on their local quality characteristics. The system evaluates each measurement's reliability using statistical data of multipath components and assigns higher weights to more reliable measurements and lower weights to measurements affected by multipath interference. This localized quality assessment improves overall estimation accuracy without requiring complete reprocessing of all data.
Solution Approach 2:
The system changes the parameter of weight coefficients dynamically based on the statistical characteristics of multipath components. By adjusting these parameters according to the measured signal conditions and stored statistical data, the system optimizes the contribution of each distance measurement to the final position estimate, resolving the contradiction between simplicity and accuracy.
Data Source
AI summary
A mobile station that is a position estimation device that estimates a position of the mobile station based on a plurality of distance measurement results measured between each of a plurality of fixed stations and the mobile station using wireless communication includes: a positioning calculation unit that calculates a coordinate-axial position of the mobile station for each coordinate axis using a position of the fixed stations and the distance measurement results in order from a coordinate axis having a largest coordinate-axial distance between the plurality of fixed stations; and a position estimation result generation unit that generates a position estimation result indicating a three-dimensional position of the mobile station based on a calculation result of the coordinate-axial position.