Inertial Sensor Fusion Calibration for Cross-Sensitivity Errors
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing inertial measurement units (IMUs) suffer from inaccuracies due to environmental conditions and cross-sensitivities, which are not adequately addressed by current calibration methods, leading to errors in the detection of physical quantities.
Innovation Solution
A method involving a fusion model that integrates characterizations of multiple inertial sensors with different types, accounting for both primary and cross-sensitivities, to create a calibration model or algorithm that compensates for reproducible and non-reproducible sensor errors, using a common reference coordinate system and potentially incorporating non-inertial sensors for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration methods are used that only consider primary sensitivity, then the calibration process is simple, but measurement precision deteriorates due to uncorrected cross-sensitivity errors
Solution Approach 1:
The calibration process is segmented into distinct phases: determining primary sensitivity characterization, determining cross-sensitivity characterization, creating separate sensor models for each, and then integrating them into a fusion model. This segmentation allows systematic handling of complex calibration requirements while maintaining manageable complexity at each step.
Solution Approach 2:
The calibration approach transitions from one-dimensional primary sensitivity correction to multi-dimensional calibration by incorporating cross-sensitivity parameters. The fusion model integrates multiple sensor types (accelerometers, gyroscopes) and their respective primary and cross-sensitivities, adding dimensional complexity that enables comprehensive error compensation and improves measurement precision.
2Measurement precision
If fusion model integrating multiple sensor types is used, then measurement precision improves through cross-sensitivity compensation, but device complexity increases
Solution Approach 1:
Multiple sensor models representing different inertial sensor types (accelerometers, gyroscopes) are merged into a single fusion model. This integration combines primary sensitivity and cross-sensitivity characterizations from all sensors, enabling unified error compensation across the entire sensor array and improving overall measurement precision through synergistic interaction of multiple sensor data streams.
Solution Approach 2:
The fusion model serves multiple functions simultaneously: it compensates for primary sensitivity errors, corrects cross-sensitivity errors, integrates data from multiple sensor types, and provides a unified calibration framework. This multi-functionality justifies the increased device complexity by delivering comprehensive measurement precision improvements that a single-function calibration approach cannot achieve.
3Reliability
If comprehensive calibration considering all sensitivities is performed, then reliability improves through error compensation, but ease of operation deteriorates due to complex calibration procedure
Solution Approach 1:
The comprehensive calibration procedure is performed as a preliminary action during system setup or manufacturing, before normal operation begins. By completing the complex characterization and model creation processes in advance, the system achieves high reliability through thorough error compensation, while the operational phase benefits from pre-computed calibration parameters that simplify real-time use.
Solution Approach 2:
The calibration system determines its own characterization parameters through automated procedures. The sensor models and fusion model are created based on measured data from the sensors themselves, enabling self-calibration without requiring external reference equipment or manual intervention. This self-service approach improves reliability through comprehensive error compensation while partially offsetting the complexity burden.
Data Source
Figure 1~2
Figure 3
AI summary
The invention relates to a method for calibrating an arrangement of inertial sensors with at least two different sensor types for detecting two different physical quantities, comprising the steps of: determining (S1/S2) a characterization of a first/second inertial sensor of a first/second sensor type with respect to its primary sensitivity; determining (S3/S4) a characterization of the first/second inertial sensor with respect to its cross-sensitivity to the physical quantity not intended to be detected by it; creating (S5) a respective processable sensor model based on the respective characterization; integrating (S6) the sensor models into a fusion model;and determining (S7) a calibration model as the inverse of the fusion model, such that processable sensor signals from the first inertial sensor and the second inertial sensor can be used as input to the calibration model and an estimate of predominant physical quantities can be used as output to the calibration model.;