Inertial Sensor Yaw Conversion for Stable Autonomous Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing autonomous navigation systems using a Kalman filter and six-axis inertial sensors face convergence issues and divergence of estimated attachment angles when the sensor's attachment angle deviates from the standard value or exceeds ±90°, hindering proper calculation of the vehicle's state.
Innovation Solution
An autonomous navigation system that includes a yaw angle range detection mechanism to convert the inertial sensor output into a virtual sensor with a yaw angle within ±90°, using a conversion function to adjust the sensor output and set initial values for the Kalman filter, ensuring rapid convergence of attachment angle estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the attachment angle of the inertial sensor deviates from the standard value, then the system can still operate, but the estimated attachment angle takes a long time to converge or converges to an incorrect value
Solution Approach 1:
The system performs preliminary detection of the yaw angle range before initiating the Kalman filter estimation. By detecting which range the yaw angle falls into and pre-setting the appropriate initial value, the system prepares the estimation process in advance, avoiding long convergence times and incorrect convergence that would occur with standard initial values when the attachment angle deviates from standard values.
Solution Approach 2:
The system changes the initial value parameter of the Kalman filter based on the detected yaw angle range. Instead of using a fixed standard initial value, the system selects different initial values corresponding to different yaw angle ranges, allowing the estimation to start from a more appropriate point and converge quickly and accurately even when the sensor attachment angle deviates from standard values.
2Reliability
If the yaw angle of the attachment angle exceeds ±90°, then the system can process the data, but the estimated attachment angle diverges without converging
Solution Approach 1:
The system segments the full yaw angle range into multiple sub-ranges (e.g., -180° to -90°, -90° to 0°, 0° to 90°, 90° to 180°). By detecting which segment the current yaw angle falls into and applying corresponding range-specific processing, the system prevents divergence that occurs when the angle exceeds ±90° while still maintaining the ability to handle the complete 360-degree range.
Solution Approach 2:
The system introduces an intermediary range detection mechanism that acts as a mediator between the raw sensor data and the Kalman filter estimation. This intermediary detects the yaw angle range and transforms the input data or initial values accordingly, preventing the estimation from diverging when the yaw angle exceeds ±90° while preserving the full adaptability to handle all possible attachment angles.
3Reliability
If a standard Kalman filter is used without range detection, then the system structure remains simple, but the state calculation is hindered when attachment angle exceeds allowable range
Solution Approach 1:
The system performs a preliminary detection of the yaw angle range before the main state calculation process. This preliminary action identifies which range the attachment angle falls into and prepares appropriate initial values or processing parameters, ensuring that the subsequent Kalman filter operation remains reliable even when the attachment angle exceeds the standard allowable range of ±90°.
Solution Approach 2:
The system changes certain parameters (initial values, processing mode) based on the detected yaw angle range. By adapting these parameters to match the actual range conditions, the system maintains high state calculation accuracy for any attachment angle while keeping the added complexity minimal, as it only involves detecting the range and selecting corresponding pre-defined parameters.
Data Source
Figure 1
Figure 2A~2B
Figure 3A~3E
AI summary
Provided is an "autonomous navigation system" that satisfactorily estimates an attachment angle of an inertial sensor even when the yaw angle of the attachment angle of the inertial sensor is large. A sensor attachment angle detection unit (13) detects a yaw angle A3 of an approximate attachment angle of a six-axis inertial sensor (11), and a sensor output conversion unit (15) converts acceleration outputs (ax, ay, az) and angular velocity outputs (ωx, (ωy, ωz) of three axes Xs, Ys, and Zs in a coordinate system of the six-axis inertial sensor (11) into accelerations (ax', ay', az) and angular velocities (ωx', ωy', ωz) of three axes Xs', Ys', and Zs in the coordinate system having a yaw angle within ±45 according to an angle range to which the detected attachment angle A3 belongs and inputs the converted accelerations and angular velocities to a Kalman filter (16).