Inertial Sensor Drift Mitigation via Periodic Signal Inversion
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Solution Overview
Problem
Linear inertial sensors are prone to errors due to drift caused by changes in spring constants and amplifier gain over time, which affect their accuracy in determining inertial information like acceleration or rotation.
Innovation Solution
The system extracts inertial information from nonlinear periodic signals using a circuitry that receives periodic analog signals from a sensor interacting with a proof mass, converts them into digital signals, and determines inertial parameters through trigonometric inversion and unwrapping processes, effectively mitigating the effects of drift by using geometric dimensions and conditioning techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If linear inertial sensors use predetermined quantities (spring constants, amplifier gain) to scale linear signals, then inertial information can be determined, but error due to drift over time increases
Solution Approach 1:
The patent changes the fundamental parameter being measured from linear signal amplitude (prone to drift) to signal period/frequency (resistant to drift). By measuring the period of oscillation rather than the amplitude, the system eliminates sensitivity to spring constant and amplifier gain variations, as these parameters affect amplitude but not the natural period of oscillation.
Solution Approach 2:
The patent replaces the mechanical scaling approach (using physical spring constants and amplifier gains) with a temporal measurement approach (measuring signal period). This substitution transitions from amplitude-based measurement to time-based measurement, which is inherently more stable against drift in mechanical and electrical components.
2Reliability
If nonlinear periodic signals are used to determine inertial information, then drift effects are mitigated, but signal processing complexity increases
Solution Approach 1:
The system uses the signal's own periodic characteristics to extract inertial information. By measuring the period of the existing periodic signal and using trigonometric relationships, the system derives displacement and acceleration without requiring external calibration or complex compensation mechanisms. The signal's periodicity serves the dual purpose of being both the measurement target and the reference for calculation.
Solution Approach 2:
Instead of directly measuring displacement or acceleration from the signal amplitude, the patent inverts the approach by measuring the signal period and then using trigonometric inversion to derive the inertial parameters. This indirect measurement approach through temporal characteristics simplifies the measurement process while improving reliability.
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
This approach allows for accurate extraction of inertial parameters such as displacement and acceleration, reducing errors associated with drift and improving the reliability of inertial measurements.
Implementation Method 1
the first sensor is a first electrode interacting with the proof mass. In some examples, the first electrode electrostatically interacts with the proof mass.
Data Source
AI summary
Systems and methods are described herein for extracting inertial information from nonlinear periodic signals. A system for determining an inertial parameter can include circuitry configured for receiving a first periodic analog signal from a first sensor that is responsive to motion of a proof mass, converting the first periodic analog signal to a first periodic digital signal, determining a result of trigonometrically inverting a quantity, the quantity based on the first periodic digital signal, and determining the inertial parameter based on the result.