Sensor Signal Filtering via Pseudo Reference Frame Transformation
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Solution Overview
Problem
Existing methods for filtering signals from sensors measuring vector physical fields, such as those used in inertial measurement units, struggle to effectively separate desired physical field measurements from undesired contributions like inherent accelerations and magnetic disturbances, leading to inaccurate orientation calculations and increased electrical consumption.
Innovation Solution
A method involving a transformation of sensor measurements into a pseudo reference frame, followed by filtering and inverse transformation, allows for the separation of physical field contributions from disturbances, utilizing a gyrometer to determine the rotational transformation operator and adaptively filtering signals to isolate the desired physical fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional filtering methods are applied to separate physical field measurements from disturbances, then measurement precision is improved, but device complexity and computational load increase
Solution Approach 1:
The filtering method segments the signal processing by separating the physical field measurement from disturbance components through coordinate transformation. The measurement is first transformed to a pseudo-reference frame where the physical field becomes stationary, allowing independent filtering of disturbance components without affecting the core measurement.
Solution Approach 2:
A pseudo-reference frame is introduced as an intermediary coordinate system between the sensor frame and the Earth reference frame. This intermediate frame serves as a mediator that simplifies the filtering process by making the physical field stationary, thereby reducing the complexity of disturbance separation while maintaining measurement precision.
2Measurement precision
If complex filtering algorithms are used to reduce disturbances, then measurement precision is improved, but electrical consumption increases
Solution Approach 1:
The coordinate transformation to the pseudo-reference frame is performed as a preliminary action before filtering. This preprocessing step simplifies the subsequent filtering operation by eliminating the time-varying nature of the physical field, thereby reducing the computational complexity and electrical consumption of the filtering algorithm while maintaining high measurement precision.
3Device complexity
If direct filtering in the sensor frame is applied, then device complexity is minimized, but measurement precision deteriorates due to coupling between physical field and disturbances
Solution Approach 1:
The pseudo-reference frame acts as an intermediary that decouples the physical field from disturbance components. By transforming measurements to this intermediate frame where the physical field is stationary, the filtering process can independently remove disturbances without affecting the physical field measurement, thereby improving precision without significantly increasing complexity.
4Measurement precision
If adaptive filtering is implemented to handle varying disturbance characteristics, then measurement precision is improved, but computational load and device complexity increase
Solution Approach 1:
The filtering approach segments the disturbance removal process into coordinate transformation and independent component filtering. This segmentation allows adaptive filtering to be applied selectively to disturbance components in the pseudo-reference frame without requiring complex adaptive algorithms to handle the coupled physical field and disturbances simultaneously, thereby improving precision while maintaining computational efficiency.
Data Source
AI summary
A method for filtering the signals arising from a sensor assembly (EC) comprising at least one measurement sensor for measuring a vector physical field which is substantially constant over time and in space in a reference frame, said sensor assembly (EC) being tied in motion to a moving frame, moving in the reference frame, the method comprising the steps consisting in:applying a first transformation (T1) to the measurements of a measurement sensor of the sensor assembly (EC) which are provided in the moving frame, to a pseudo reference frame, with the aid of a first change-of-frame operator (R(t)) by rotation between the moving frame and the pseudo reference frame; andapplying a filtering (FILT) to the measurements thus transformed in the pseudo reference frame; and applying a second transformation (T2), the inverse of said first transformation, to the measurements filtered by said filtering (FILT), from the reference frame to the moving frame, with the aid of a second change-of-frame operator (R−1(t)) by rotation between the pseudo reference frame and the moving frame, the inverse of said first operator (R(t)).