Visual Data Tagging for GNSS-Denied Location Heatmaps
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Solution Overview
Problem
In environments where Global Navigation Satellite System (GNSS) signals are not available, such as indoor spaces and urban canyons, existing methods for determining a mobile device's location are inadequate, leading to challenges in providing accurate location-based services.
Innovation Solution
The technique involves tagging visual data, such as images or videos, with wireless and sensor measurement information, which is then sent to a crowdsourcing server to determine the location based on visual features and sensor data, allowing for the creation and updating of heatmaps that associate wireless measurements with locations, enabling location determination even in GNSS-denied environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If satellite-based positioning is used, then location accuracy is improved in outdoor environments, but it becomes ineffective in indoor environments and urban canyons where direct line of sight to satellites is blocked
Solution Approach 1:
The patent divides the positioning system into multiple independent components: visual feature extraction from images, sensor data acquisition (accelerometer, gyroscope, magnetometer, barometer), and wireless signal detection. Each component operates independently to provide location information, allowing the system to function in various environments including indoor and urban canyon settings where satellite-based positioning fails
Solution Approach 2:
The patent combines multiple data sources including visual features from captured images, sensor measurements (motion, orientation, pressure), and wireless signal information into a unified location determination system. This integration creates a robust positioning solution that maintains reliability across different environments by compensating for the limitations of individual sensing modalities
2Measurement precision
If manual updates of location data are performed, then heatmap accuracy is maintained, but the system complexity and time consumption increase significantly
Solution Approach 1:
The patent implements an automated system where mobile devices autonomously capture visual data, extract location information from visual features, and contribute this data to heatmap generation. The system self-updates heatmaps by processing crowd-sourced visual data from multiple devices, eliminating the need for manual field surveys and significantly reducing update time while maintaining or improving accuracy through aggregated data
3Measurement precision
If visual data tagging with wireless and sensor information is implemented, then location determination accuracy in GNSS-denied environments is improved, but data processing complexity increases
Solution Approach 1:
The patent performs visual feature extraction and tagging of visual data with sensor and wireless information at the mobile device level before data is transmitted to the server. This preliminary processing reduces the complexity of server-side operations by pre-organizing and labeling data with relevant location context, enabling more efficient centralized processing while maintaining high location determination accuracy
Data Source
AI summary
Techniques describe tagging visual data (e.g., image and/or video data) with wireless and sensor measurement information by a mobile device. Tagged visual data may be sent to a server, such as a crowdsourcing server. Techniques further describe receiving visual data from a device, wherein the visual data is tagged with information comprising source identifying information associated with an at least one signal emitting device, identifying at least one visual feature from the visual data, determining a coordinate on a map at which the visual data was acquired based on identifying the at least one visual feature from the visual data, and associating the coordinate on the map with the information associated with the at least one signal emitting device.