RTT-Based Stopped State Detection for Mobile Devices
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Solution Overview
Problem
Existing methods for determining if a mobile device is in a stopped state, such as using accelerometers, are vulnerable to sudden movements and device shaking, necessitating an improved system for accurately assessing device movement.
Innovation Solution
The use of round trip time (RTT) measurements between a mobile device and access points (APs) to determine if a device is in a stopped state, incorporating multiple APs and combining RTT measurements with other data sources like GNSS and accelerometer data, and applying filtering techniques like particle or Kalman filters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If accelerometer measurements are used for stopped detection, then the system can detect device movement, but the detection is vulnerable to false positives from sudden movements and device shaking
Solution Approach 1:
The patent segments the stopped state detection into multiple independent measurement components: RTT measurements from multiple access points, accelerometer measurements, and barometer measurements. Each component independently assesses movement, and the system integrates these segmented measurements to make a final determination. This segmentation allows the system to cross-validate measurements and reduce false positives from sudden movements or device shaking that might affect a single sensor type.
Solution Approach 2:
The patent merges multiple data sources including RTT measurements from multiple access points, accelerometer data, and barometer data into a unified stopped state detection system. By combining these diverse measurement types, the system achieves more reliable detection than any single sensor could provide alone. The merging of measurements allows the system to distinguish between actual device movement and false positive signals from sudden movements or shaking.
2Measurement precision
If multiple data sources are combined for stopped detection, then the accuracy improves, but the system complexity increases
Solution Approach 1:
The patent implements a universal measurement framework where multiple sensors (RTT, accelerometer, barometer) serve the same ultimate function of determining stopped state. Each sensor type is multi-functional in that it can detect various types of movement (linear, angular, vertical), and the system processes them through a unified algorithm that applies the same logical criteria regardless of which sensor triggered the measurement. This universality reduces complexity by providing a consistent processing approach rather than separate specialized routines for each sensor type.
Solution Approach 2:
The system performs self-service by automatically selecting and weighting the most reliable measurements from available data sources based on their inherent characteristics and current performance. The measurement integration algorithm autonomously determines which sensors provide the most trustworthy data in given conditions and adjusts their contribution to the final stopped state determination without requiring manual configuration or external intervention. This self-service capability reduces system complexity by eliminating the need for complex manual tuning and configuration procedures.
Data Source
AI summary
Methods, devices, and systems are described for determining whether a mobile device is in a stopped state based at least in part on round trip time (RTT) measurements between the device and at least one access point. The stopped state determination may be based on RTT measurements alone, or on RTT measurements in combination with other positioning and movement measurements. Further, filtering such as particle and Kalman filtering may be used to improve determination of whether the device is in a stopped state.