Location Reference Updating for Low-Sensor Mobile Positioning
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Solution Overview
Problem
Existing mobile device location estimation systems face accuracy issues, especially in environments with repeated patterns, and are hindered by the need for high-performance sensors, which increases production costs.
Innovation Solution
A location estimation server collects data from a high-performance mobile device, generates new reference data based on the collected information, and distributes it to a second mobile device with lower-performance sensors, allowing the second device to adjust its direction and estimate its location accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sensor with high accuracy is mounted in the mobile device, then location estimation accuracy is improved, but production cost increases
Solution Approach 1:
A server acts as an intermediary between mobile devices with low-performance sensors and the location estimation system. The server collects data from multiple mobile devices, generates accurate reference data, and provides it to devices with lower-performance sensors, enabling accurate location estimation without requiring expensive high-performance sensors in each device
Solution Approach 2:
The system creates reference data that copies the location information environment characteristics from areas where high-performance sensors are used. This reference data is then distributed to mobile devices with lower-performance sensors, allowing them to estimate locations accurately by comparing their sensor data against the reference data without needing the expensive original sensors
2Ease of operation
If pre-stored location data is used for estimation, then the system operates without user input, but accuracy decreases when the device is moved to a different location
Solution Approach 1:
The system implements feedback by continuously collecting location data from multiple mobile devices, comparing it with reference data, calculating errors, and updating the reference data accordingly. This feedback loop ensures that the reference data remains accurate even when devices move to different locations or when environmental changes occur
Solution Approach 2:
The reference data is made dynamic rather than static. The system periodically updates the reference data based on new collected data and error calculations, allowing the location estimation system to adapt to changes in the environment and device locations over time, maintaining accuracy without requiring user re-input
3Measurement precision
If location data is collected from multiple mobile devices, then reference data accuracy is improved, but system complexity increases
Solution Approach 1:
The server performs multiple functions: collecting data from mobile devices, generating reference data, calculating errors, updating reference data, and distributing it to devices. This multi-functionality consolidates complex operations into a single centralized system, managing complexity rather than increasing it across the distributed network
Data Source
AI summary
A server may include one or more processors, and memory storing instructions that, when executed by the one or more processors, cause the server to, collect, from a first mobile device, location information associated with a specified area, store reference data, associated with a relative location between a second mobile device and the specified area, determine, based on at least one of the location information or the stored reference data, whether an error calculated satisfies a threshold value, generate, based on the determination, new reference data, and cause, based on the new reference data and the location information, the second mobile device to adjust driving direction.