Mobile Device Location Accuracy in GPS-Drift Environments
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Solution Overview
Problem
In bandwidth-constrained environments, traditional GPS-based location determination for mobile devices is unreliable in areas like urban canyons due to data drift, leading to inaccurate location identification.
Innovation Solution
Mobile devices acquire both GPS and IMU data, compress the IMU data to reduce dimensionality, and transmit it alongside GPS data to a server, which reconstructs the IMU data and combines it with GPS data for accurate location determination, using techniques like variational auto encoding or fingerprinting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If GPS data is used for location determination in urban canyons, then the system can operate with low device complexity and power consumption, but the location accuracy deteriorates due to GPS data drift
Solution Approach 1:
The patent combines GPS data with IMU (Inertial Measurement Unit) data to determine device location. The server receives both GPS coordinates and IMU sensor data (accelerometer, gyroscope, magnetometer), processes them together, and uses data fusion algorithms to calculate accurate location even in urban canyon environments where GPS alone drifts.
Solution Approach 2:
The server acts as an intermediary that receives compressed IMU data from the mobile device, reconstructs the original sensor data, and processes it alongside GPS data. This intermediary processing resolves the contradiction by enabling accurate location determination without requiring the mobile device itself to have complex processing capabilities.
2Measurement precision
If full-dimensional IMU data is transmitted to the server, then location determination accuracy is improved, but communication bandwidth consumption increases
Solution Approach 1:
The patent extracts only the essential features from the full-dimensional IMU data for transmission. The mobile device processes the raw sensor data and extracts key characteristics (such as motion patterns, orientation changes) that are most relevant for location determination, then transmits only this compressed feature set to the server.
Solution Approach 2:
The mobile device performs preliminary processing of IMU data before transmission, compressing and feature-extracting the sensor data in advance. This preliminary action reduces the data volume that needs to be transmitted over the network while preserving the essential information needed for accurate location determination.
3Measurement precision
If IMU data is acquired and processed at the mobile device, then location accuracy in urban canyons is improved, but device power consumption increases
Solution Approach 1:
The mobile device extracts only the necessary features from IMU data rather than processing and transmitting all raw sensor data. This extraction approach minimizes the computational effort required at the device while still providing sufficient information for accurate location determination when combined with GPS data at the server.
Solution Approach 2:
The system performs partial processing of IMU data at the mobile device (feature extraction) and completes the full processing at the server. This division of labor allows the mobile device to use minimal power while still enabling accurate location determination through the combined processing power of both device and server.
Data Source
AI summary
Embodiments of the present disclosure support improving determination of a location of a driver device that performs bandwidth constrained communication with a server, based on sensor data acquired by the driver device. The driver device reduces dimensionality of the acquired sensor data before transmitting the sensor data to the server over a communication network. The server receives GPS data and compressed sensor data from the driver device, and determines a quality metric related to the GPS data. Based on the quality metric, the server increases dimensionality of the compressed sensor data to reconstruct original sensor data acquired by the driver device. The server than augments the GPS data with the reconstructed sensor data, and determines location information of the driver device based on the augmented data.