Mobile Device Location Accuracy via Nearby Sensor Fusion
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Solution Overview
Problem
Mobile devices face inaccuracies in location determination due to unreliable sensor measurements, such as those caused by metal objects or multipath reflections, which existing technologies fail to detect effectively, leading to incorrect location estimates.
Innovation Solution
A method where a mobile device communicates with nearby devices to receive concurrent sensor measurements, applies statistical analysis to identify outliers, and excludes unreliable measurements from its location determination, using techniques like RANSAC to enhance accuracy and account for local effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor measurements from a single mobile device are used for location determination, then the device can operate independently, but the location accuracy deteriorates due to unreliable measurements from metal objects or multipath reflections
Solution Approach 1:
The patent combines sensor measurements from multiple mobile devices to improve location determination reliability. By merging data from nearby devices, the system creates a more robust location estimate that is less susceptible to corruption from metal objects or multipath reflections affecting a single device's sensors.
Solution Approach 2:
The patent introduces statistical analysis as an intermediary process between raw sensor measurements and location determination. This mediator identifies and filters out corrupted measurements by comparing sensor data across multiple devices, removing the harmful effects of unreliable measurements before final location calculation.
2Measurement precision
If sensor measurements are filtered to exclude unreliable data, then location accuracy improves, but the complexity of measurement processing increases
Solution Approach 1:
The system performs self-diagnosis by having each mobile device compare its own sensor measurements against measurements from nearby devices. The statistical analysis automatically identifies which measurements are outliers or corrupted, allowing the system to self-correct without external intervention or complex manual filtering processes.
Solution Approach 2:
The patent applies statistical analysis to all sensor measurements from multiple devices, performing more analysis than strictly necessary for simple cases. This excessive action ensures that even subtle corruptions from metal objects or multipath reflections are detected and filtered, prioritizing measurement precision over processing efficiency.
Data Source
AI summary
Methods and systems are disclosed for evaluating the reliability of sensor measurements of environmental properties used for deriving the location of a mobile device. A mobile device can receive measurements of environmental properties made sensors of one or more other mobile devices concurrently with real-time measurements of the environmental properties made by sensors of the mobile device. The mobile device can determine that each of the other mobile devices is within a locality threshold of the mobile device. The mobile device can determine that a difference between at least one of the real-time measurements and a metric of the received measurements corresponds to a statistical likelihood that the at least one of the real-time measurements is unreliable. Any of the real-time measurements that are determined to be unreliable can be excluded from a location determination of the mobile device derived from the real-time measurements of the environmental properties.