Partial Phase Vectors for Location System Accuracy
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Solution Overview
Problem
Location systems face accuracy issues due to partial phase vectors, which are incomplete data sets resulting from packet exchanges failures between access points and client devices, often caused by RF interference, device faults, or other environmental factors, making it difficult to diagnose and remediate errors effectively.
Innovation Solution
The system captures partial phase vector data and associated information across multiple dimensions, applies machine learning models like unsupervised learning or clustering to determine correlations, and presents visualizations to identify the root cause of errors, enabling automatic remediation actions to improve location system accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If angle-based techniques with antenna arrays are used to determine location, then location accuracy can be achieved under ideal conditions, but the system becomes vulnerable to RF interference and packet exchange failures that degrade accuracy
Solution Approach 1:
The system captures partial phase vector data and associated metadata, then uses machine learning models to analyze patterns and provide feedback about system health and accuracy degradation sources. This feedback loop enables continuous monitoring and remediation of issues affecting location accuracy.
Solution Approach 2:
Machine learning models serve as intermediaries between the raw partial phase vector data and the location determination process. These models analyze the data to identify patterns and causes of accuracy degradation, enabling the system to remediate issues without directly altering the core angle-based location technique.
2Measurement precision
If complete phase vectors are required for accurate location determination, then measurement precision is maintained, but the system cannot operate effectively when packet exchanges fail or RF interference occurs
Solution Approach 1:
The system accepts and processes partial phase vectors (incomplete data) rather than requiring complete phase vectors. Machine learning models analyze these partial data sets to determine location information and identify causes of incompleteness, allowing the system to operate under degraded conditions while maintaining adaptability.
Solution Approach 2:
The system changes the parameter requirement from complete phase vectors to partial phase vectors, enabling operation under a wider range of conditions. Machine learning models compensate for the reduced data quality by identifying patterns and making accurate determinations despite incomplete information.
3Ease of repair
If the system captures and analyzes partial phase vector data across multiple dimensions using machine learning, then the ability to diagnose and remediate errors improves, but device complexity increases
Solution Approach 1:
The system performs self-diagnosis by capturing partial phase vector data and using machine learning models to automatically identify causes of location accuracy degradation. This self-service capability reduces the need for external intervention and manual troubleshooting, making error diagnosis easier despite the increased complexity of the diagnostic system itself.
Data Source
AI summary
Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.