Positioning Accuracy via Base Station Selection
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Solution Overview
Problem
Existing local positioning systems for athletes and objects in sports environments suffer from inaccuracies due to multipath and non-line-of-sight errors, which can lead to significant errors in position calculation even when a single base station's measurement is corrupted.
Innovation Solution
A method that predicts the position and orientation of an object of interest, selects only base stations capable of receiving line-of-sight signals based on the radiation pattern and predicted position, and excludes others to reduce NLOS and multipath errors, using time of arrival or time difference of arrival measurements from a subset of base stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If measurements from all base stations are used to calculate position, then more measurement data is available for position calculation, but positioning accuracy deteriorates due to NLOS and multipath errors from base stations with obstructed signals
Solution Approach 1:
The patent extracts and removes measurements from base stations that are likely to provide NLOS or multipath errors. By identifying base stations with obstructed signals (those blocked by the object of interest or other objects), the system excludes these problematic measurements from the position calculation, thereby improving positioning accuracy while reducing the total number of measurements used.
Solution Approach 2:
The patent performs preliminary identification of base stations that will provide good quality measurements before the actual position calculation. By predicting which base stations are likely to have LOS signals based on object position, orientation, and radiation patterns, the system prepares a filtered set of reliable measurements in advance, avoiding the need to process and discard poor quality measurements later.
2Measurement precision
If base stations with potential NLOS errors are excluded from position calculation, then positioning accuracy improves, but the complexity of determining which base stations to exclude increases
Solution Approach 1:
The system uses the object's own predicted position and orientation, combined with knowledge of its radiation pattern and the positions of other objects in the environment, to automatically determine which base stations will provide good quality measurements. This self-characterizing approach eliminates the need for external manual assessment or complex external evaluation systems.
Solution Approach 2:
The patent performs preliminary assessment of base station quality by predicting which base stations are likely to have LOS signals based on object position, orientation, and radiation patterns before actual position calculation. This advance filtering simplifies the subsequent position calculation by pre-identifying reliable measurements.
3Reliability
If the radiation pattern and object orientation are considered to select base stations, then NLOS errors are reduced, but additional computational resources are required for prediction and pattern analysis
Solution Approach 1:
The patent performs preliminary prediction of object position and orientation, and preliminary identification of suitable base stations, before the actual position calculation. By doing this filtering work in advance, the system avoids the need for complex real-time analysis during position calculation, reducing computational energy consumption during the critical measurement phase.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances position calculation accuracy by excluding base stations prone to errors, reducing computational costs and improving reliability, while also considering neighboring objects and signal strengths to validate line-of-sight conditions.
Implementation Method 1
time-of-arrival or time-difference-of-arrival measurements of electromagnetic waves. These electromagnetic waves travel between base stations with fixed and known positions and mobile transponders
Implementation Method 2
a radiation pattern of a system comprising the object of interest and a mobile transponder attached to the object of interest
Implementation Method 3
time-of-arrival or time-difference-of-arrival measurements of electromagnetic waves
Data Source
AI summary
A method for calculating a position of an object of interest in an environment. The method includes: predicting a position and an orientation of the object of interest in the environment; selecting a subset of base stations among a set of base stations located within the environment, by using the predicted position and orientation, and a radiation pattern of a system including the object of interest and a mobile transponder attached to the object of interest; and calculating an actual position of the object of interest, using time of arrival or time difference of arrival measurements between the base stations of the subset and the mobile transponder.