Sensor Data Correction via Orientation Angle Feedback
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Solution Overview
Problem
Existing methods for evaluating sensor data, such as those using Kalman filters, can result in large errors due to small deviations in sensor orientation relative to motion direction, especially in handheld or vehicle-based applications, where the sensor position changes, leading to inaccuracies in navigation systems.
Innovation Solution
A method that corrects sensor data using a mathematical model to maintain a predefined angle between sensor orientation and motion direction, utilizing application criteria like minimum speed and sensor position stability, with the option to adjust the model based on these criteria, and employing filters like Kalman filters to reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is processed using mathematical models like Kalman filters, then measurement precision is improved, but errors accumulate due to integration over time
Solution Approach 1:
The patent implements feedback by continuously monitoring the angle between sensor orientation and motion direction, and using this information to correct sensor data processing. The system compares the actual angle with the expected angle and adjusts the mathematical model parameters accordingly, creating a closed-loop correction mechanism that prevents error accumulation.
Solution Approach 2:
The patent changes parameters of the mathematical model dynamically based on the detected angle between sensor orientation and motion direction. When the angle deviates from the expected range, the system adjusts the model parameters (such as process noise covariance) to compensate for the orientation discrepancy, thereby maintaining navigation accuracy.
2Measurement precision
If the sensor orientation relation to motion direction is not maintained, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system performs self-service by automatically detecting and correcting orientation deviations without requiring external intervention or additional sensors. The acceleration and rotation rate sensors work together to self-correct the sensor orientation relationship, eliminating the need for complex external alignment systems or additional hardware.
Solution Approach 2:
The patent makes the sensor system universal by enabling the same acceleration and rotation rate sensors to serve multiple functions: they not only detect motion but also maintain orientation relationship and correct their own data processing. This multi-functionality eliminates the need for separate orientation sensors or alignment mechanisms.
3Measurement precision
If additional sensors are added to maintain sensor orientation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent achieves multi-functionality by enabling the existing acceleration and rotation rate sensors to perform orientation maintenance and self-correction. The rotation rate sensor provides both angular velocity data and orientation information, while the acceleration sensor contributes to both motion detection and orientation validation, eliminating the need for separate orientation sensors.
Solution Approach 2:
The system merges the functions of motion detection and orientation maintenance into a single integrated processing approach. By combining the data from acceleration and rotation rate sensors in a unified mathematical model, the system achieves orientation accuracy without requiring separate dedicated sensors for each function.
Data Source
AI summary
A method for evaluating sensor data. Raw sensor data and/or processed sensor data are initially read in from an acceleration sensor and a rotation rate sensor. Measured data are subsequently ascertained from the raw sensor data and/or the processed sensor data. In addition, at least one application criterion is ascertained. The measured data are then corrected based on a mathematical model. In the correction, an angle between a direction of a sensor orientation and a motion direction is maximally changed by a predefined value per time unit when the application criterion is met. The corrected measured data are subsequently output.