Mobile Device Motion State for Position Estimate
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Solution Overview
Problem
Existing positioning technologies for mobile devices using radio signals face challenges in achieving accurate and reliable location estimates due to the lack of secure data verification and excessive data transmission, especially in online modes where radio measurements are processed and filtered without reliable mechanisms.
Innovation Solution
A method that involves taking radio measurements and motion data to determine the motion state of a mobile device, which is then used to improve position estimates by providing this information to a server for more accurate positioning without the need for excessive data transfer, utilizing motion sensors like inertial sensors to estimate the motion state locally and reduce raw data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion measurement data is transmitted from mobile device to server, then position estimate accuracy is improved, but data transmission volume increases
Solution Approach 1:
The patent extracts only the essential motion state information (e.g., stationary, walking, running, vehicle motion) from the raw motion measurement data obtained by the mobile device's sensors. Instead of transmitting the complete raw acceleration and gyroscope data streams, the system processes the data locally on the mobile device to determine motion state categories, and transmits only these extracted motion state indicators to the server. This extraction principle resolves the contradiction by maintaining position accuracy through motion state information while dramatically reducing the data transmission volume.
Solution Approach 2:
The patent introduces motion state determination as an intermediary processing step between raw motion measurement data collection and position estimation. The mobile device acts as an intermediary that processes raw sensor data locally to derive motion state information, which then serves as a mediator input for the server's position estimation algorithm. This intermediary approach allows the system to convey essential motion context to the server without transmitting the full raw data stream, thus improving position accuracy while minimizing data transmission.
2Reliability
If radio measurements and motion data are processed locally, then positioning reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the positioning system into distinct functional components: the mobile device handles motion data collection and motion state determination, while the server performs radio measurement processing and final position estimation. This segmentation allows each component to focus on specific tasks, improving overall positioning reliability through specialized processing. The mobile device's complexity is kept manageable by only performing motion state classification rather than complete position estimation, while the server handles the computationally intensive radio signal processing.
Solution Approach 2:
The patent implements self-service by enabling the mobile device to autonomously determine its own motion state using its built-in motion sensors and processing capabilities. The device serves itself by collecting raw motion data, processing it through motion state determination algorithms, and generating motion state indicators without requiring external assistance. This self-service approach improves positioning reliability by ensuring accurate motion state information is available locally, while avoiding the need for additional external devices or services.
3Measurement precision
If motion state determination is added to positioning process, then position estimate accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by determining the motion state in advance of the position estimation process. The mobile device continuously monitors motion sensors and determines motion state categories before radio measurements are taken or processed. This preliminary motion state determination provides contextual information that can be immediately applied to enhance position estimation accuracy without adding significant processing delays during the actual positioning operation. The motion state information is prepared beforehand and can be used to adjust positioning algorithms in real-time.
Solution Approach 2:
The patent implements periodic action by updating motion state determination at regular intervals rather than continuously processing raw motion data. The system periodically samples motion sensors and updates motion state categories at optimized frequencies that balance accuracy requirements with processing time constraints. This periodic approach ensures that motion state information remains current enough to improve position estimation accuracy while avoiding excessive processing overhead that would increase latency in the positioning system.
Data Source
AI summary
Described is a method that includes taking radio measurements of radio node signals observable at a mobile device; obtaining motion measurement data indicative of motion of the mobile device; determining, based on the motion measurement data, a motion state of the mobile device; and providing the radio measurements taken or information representative thereof and the motion state or information representative thereof. Described is also a method that includes obtaining radio measurements of radio node signals observable at a mobile device or information representative thereof obtaining a motion state of the mobile device, the motion state having been determined based on motion measurement data indicative of motion of the mobile device, or information representative thereof determining a position estimate of the mobile device at least based on at least some radio measurements or information representative thereof and the obtained motion state of the mobile device or the information representative thereof.