Trusted-GPS Region Detection for Indoor Mobile Localization
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Solution Overview
Problem
Indoor navigation in mobile devices faces challenges with inaccurate and unreliable GPS and cellular signals, leading to delays and resource-intensive data processing, especially in lower-quality infrastructure environments.
Innovation Solution
A method and system that identifies and utilizes 'trusted-GPS' regions within indoor areas through crowd-sourced data fusion of fingerprint data, allowing for GPS-based geofencing and positioning, minimizing processor and memory usage by leveraging areas with reliable GPS signals, such as near skylights or large windows, and applying this data with higher weighting within GPS-trusted regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data fusion of fingerprint data is used for indoor localization, then localization accuracy is improved, but processor and memory resource usage increases
Solution Approach 1:
The system divides the indoor environment into distinct regions with different GPS reliability characteristics. Within trusted-GPS regions, GPS data is used with higher weighting or exclusively, while in non-trusted regions, fingerprint data fusion is employed. This spatial variation in processing strategy optimizes the balance between localization accuracy and resource consumption based on local signal conditions.
Solution Approach 2:
The indoor area is segmented into trusted-GPS regions and non-trusted regions based on GPS signal quality assessment. This segmentation allows the system to apply different localization strategies in different segments, using resource-intensive data fusion only where necessary and GPS-based methods where reliable, thereby reducing overall computational burden while maintaining accuracy where possible.
2Measurement precision
If data fusion processing is applied continuously, then localization accuracy is maintained, but processing time increases
Solution Approach 1:
Instead of continuous data fusion processing, the system periodically assesses GPS signal quality and switches between GPS-based and fingerprint-based localization methods. Within trusted-GPS regions, the system can rely on GPS updates at standard intervals without continuous fingerprint data fusion, significantly reducing processing time while maintaining acceptable localization accuracy through periodic re-assessment of position.
3Use of energy by moving object
If GPS data is used in indoor areas, then resource consumption is reduced, but signal reliability deteriorates
Solution Approach 1:
The system dynamically adjusts the weighting and usage of GPS data based on real-time signal quality assessment. In trusted-GPS regions where signal reliability is acceptable, GPS data is used with high or full weighting to minimize resource consumption. In regions where GPS signal reliability deteriorates, the system automatically reduces GPS weighting and increases reliance on fingerprint data, ensuring continuous reliable localization adapts to changing environmental conditions.
Data Source
AI summary
A method and system for localizing a mobile device having a processor and a memory. The method comprises, using the processor, localizing the mobile device during navigation of a sequence of positions along an indoor area based on a data fusion of fingerprint data, detecting, using the processor, a boundary of a trusted-global positioning system (trusted-GPS) positioning region within the indoor area, and upon navigating to the boundary, localizing the mobile device based on GPS position data acquired at the memory of the mobile device.