Mobile Device Direction Estimation Using Gravity-Referenced Inertial Filtering
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Solution Overview
Problem
Conventional methods for estimating the direction of motion using GPS and inertial sensors face inaccuracies due to noise and unreliable sensor readings, especially when smartphones are carried in different positions, leading to false positives and inaccuracies in pedestrian navigation.
Innovation Solution
A mobile device equipped with inertial sensors processes acceleration data by removing static bias and noise, determining the direction of gravity, and calculating displacement values along orthogonal axes, with user input to account for device placement, to accurately estimate direction of motion regardless of position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS and inertial sensors are used to estimate direction of motion, then localization capability is provided, but measurement accuracy deteriorates due to noise and unreliable sensor readings
Solution Approach 1:
The patent extracts and removes static bias and noise components from the raw acceleration data obtained from inertial sensors. By separating the useful motion signal from the harmful static bias and noise, the system achieves accurate direction estimation without being affected by sensor placement position or environmental interference.
Solution Approach 2:
The patent introduces an intermediary processing stage that transforms raw acceleration data into corrected acceleration data by removing static bias and noise. This intermediary processing acts as a mediator between the noisy sensor input and the final direction estimation, enabling accurate localization despite imperfect sensor readings.
2Device complexity
If inertial sensor data is processed directly without correction, then processing simplicity is maintained, but measurement precision deteriorates due to static bias and noise
Solution Approach 1:
The patent performs preliminary correction of the acceleration data by removing static bias and noise before using the data for direction estimation. This preliminary action ensures that the subsequent processing works with clean, accurate data, improving measurement precision without significantly increasing overall system complexity.
3Ease of operation
If smartphone is carried in different positions, then ease of operation is improved, but measurement precision deteriorates due to position-dependent sensor readings
Solution Approach 1:
The patent extracts and removes the static bias component from acceleration data, which is the main source of position-dependent errors. By eliminating this static offset, the system becomes insensitive to the smartphone's carrying position, allowing users to operate the device freely without affecting measurement accuracy.
Solution Approach 2:
The patent changes the parameter representation by transforming raw acceleration data into corrected acceleration data through bias removal and noise filtering. This parameter transformation makes the measurement system invariant to device orientation and placement, enabling accurate direction estimation regardless of how the smartphone is carried.
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
The solution provides accurate direction estimation free from errors, suitable for both indoor and outdoor localization, by filtering noise and static bias from acceleration data and integrating it to determine true displacement values.
Implementation Method 1
a data stream of acceleration signals corresponding to motion of the user is obtained from an inertial sensor in the mobile device
Implementation Method 2
a value of gravity and a direction of the gravity are determined from the corrected acceleration values
Data Source
AI summary
A mobile device and a method for estimation of direction of motion of a user are described. The mobile device comprises an inertial sensor to capture acceleration signals based on motion of the user and a direction estimation module. The direction estimation module determines direction of gravity based on filtering acceleration values obtained from captured the acceleration signals using a low-pass filter to identify a plane orthogonal to the direction of gravity. The plane orthogonal to the gravity comprises two orthogonal axes orthogonal to the direction of gravity. Further, displacement values are evaluated based on a user input for placement of the mobile device with respect to user's body, and integration of the acceleration values across the two orthogonal axes with respect to time. A direction of motion of the user is estimated based on a ratio of the displacement values along the two orthogonal axes.