Mobile Device Motion State Detection via Gravity Vector Orthogonal Projection
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Solution Overview
Problem
Existing mobile device motion detection technologies face challenges in accurately distinguishing between static and dynamic states due to the influence of gravity and sensor biases, leading to reduced sensitivity in motion detection.
Innovation Solution
The method involves determining an accelerometer signal vector representing the force due to gravity, rotating it to align with a vertical axis, and analyzing data orthogonal to this vector to exclude gravity and bias effects, thereby enhancing sensitivity in detecting motion states by integrating vector components over time and verifying with GPS data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If accelerometer data is used to detect motion states, then motion detection capability is provided, but gravity and sensor biases reduce detection sensitivity and accuracy
Solution Approach 1:
The patent extracts and removes the gravity component from accelerometer data by determining a signal vector representing gravity and bias, then projecting accelerometer measurements onto a plane orthogonal to this vector. This extraction isolates the harmful gravity and bias effects, allowing them to be excluded from motion detection calculations, thereby improving motion detection sensitivity without being affected by these constant or slowly varying factors.
2Reliability
If traditional accelerometer analysis is used, then motion detection is performed, but false classifications of static and moving states occur
Solution Approach 1:
The patent introduces an intermediary coordinate transformation process that rotates the accelerometer data into a reference frame where the z-axis aligns with the determined gravity signal vector. This intermediary transformation serves as a mediator between the raw accelerometer data and the final motion state classification, enabling reliable distinction between static and dynamic states by eliminating the confounding influence of gravity and bias before classification decisions are made.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach achieves high sensitivity in detecting both horizontal and vertical movements, allowing for precise determination of motion states and reducing false static or moving state classifications.
Implementation Method 1
an accelerometer that measures linear acceleration within a local inertial frame
Implementation Method 2
a three axis magnetometer
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a motion state of a mobile device. Accelerometer data is received from accelerometer sensors onboard the mobile device, wherein the accelerometer data represents acceleration of the mobile device in three-dimensional space. An accelerometer signal vector representing at least a force due to gravity on the mobile device is determined. Two-dimensional accelerometer data orthogonal to the accelerometer signal vector is calculated. A motion state of the mobile device is determined based on the two-dimensional accelerometer data.