Positioning Engine Anomaly Detection with Locator Confidence Indicators
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional positioning systems fail to efficiently detect and correct anomalies caused by misaligned or malfunctioning anchor points, leading to incorrect position determinations of mobile devices.
Innovation Solution
A method that incorporates confidence indicators with location indicators to determine if a confidence criterion is met, storing anomaly indicators in a cache when the criterion is not met, and generating alert messages based on evaluations of these indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional positioning systems use basic location indicators without additional verification, then the system operates with simple processing, but anomalies from misaligned or malfunctioning anchor points cannot be efficiently detected
Solution Approach 1:
The patent introduces confidence indicators as an intermediary element between location indicators and position determination. These confidence indicators act as a mediator that evaluates the reliability of each location indicator without requiring complex anomaly detection algorithms. The positioning engine acquires confidence indicators from locator devices, evaluates them against confidence criteria, and uses the results to identify anomalies in the positioning data, thereby improving reliability while maintaining manageable system complexity.
2Measurement precision
If the positioning system continuously monitors all location indicators for anomalies, then detection accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies local quality by evaluating confidence indicators individually for each location indicator rather than processing all data uniformly. Each location indicator is assessed against its specific confidence criterion, allowing the system to quickly identify and flag only those indicators that fail the confidence test. This localized evaluation approach maintains high detection accuracy while minimizing processing time, as the system does not need to perform complex continuous monitoring on all data points.
3Reliability
If anomaly indicators are stored continuously in a cache for each locator device, then a history of anomalies can be tracked, but memory requirements and data management complexity increase
Solution Approach 1:
The patent extracts only the essential anomaly information into a cache structure, storing anomaly indicators only when confidence criteria are not met. Rather than continuously storing all location indicator data, the system extracts and stores only the problematic cases where anomalies are detected. This selective extraction approach enables effective anomaly history tracking while keeping memory requirements and data management complexity to a minimum.
Data Source
AI summary
A method for detecting anomalies in a positioning system comprises receiving, for a plurality of locator devices (ANC1, ANC2, ANC3, ANC4), respective location indicators associated with at least one mobile device (TG1, TG2, TG3), determining a position of the at least one mobile device (TG1, TG2, TG3) based on the received location indicators, acquiring, for at least one of the location indicators received, a confidence indicator associated with the at least one of the location indicators, determining, for each acquired confidence indicator, whether a confidence criterion is met, and storing an anomaly indicator in an anomaly cache, if the confidence criterion is not met, wherein each anomaly indicator is associated with the locator device, for which the location indicator is received; and generating an anomaly alert message for at least one of the locator devices based on an evaluation of the anomaly indicators that are stored for the at least one of the locator devices.