Inertial Instrument Self-Calibration via Bias Estimator
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Inertial instruments, such as gyroscopes and accelerometers, face performance degradation due to bias and bias drift, which existing technologies often fail to minimize effectively without relying on external sources of accurate positional information like GPS signals, especially in environments where such signals are unavailable.
Innovation Solution
A self-calibrating inertial measurement apparatus that uses two inertial instruments to generate input signals and calculates bias correction signals based on measurements during specific time intervals where the sign of the bias error signals changes, allowing for internal bias correction without external data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS-based bias correction is used, then measurement precision is improved, but reliability deteriorates because GPS signals are not always available
Solution Approach 1:
The system uses itself to correct its own bias errors by employing multiple inertial instruments that measure the same physical quantity. Each instrument's output is used to calculate bias correction signals for itself and other instruments, eliminating dependency on external GPS sources and enabling autonomous operation in GPS-denied environments.
Solution Approach 2:
The patent introduces a bias estimator as an intermediary component that processes outputs from multiple inertial instruments and generates bias correction signals. This mediator enables cross-calibration between instruments by using their collective measurements to identify and correct individual instrument biases without requiring external reference sources.
2Reliability
If multiple inertial instruments are used for self-calibration, then reliability is improved, but device complexity increases
Solution Approach 1:
Each inertial instrument in the system serves multiple functions: it acts as both a measurement device and a reference source for calibrating other instruments. The outputs from these instruments are universally processed by the bias estimator to generate corrections for the entire system, maximizing the utility of each component and reducing the need for additional dedicated calibration hardware.
Data Source
Figure 1
Figure 2~3
AI summary
An exemplary inertial measurement apparatus incorporates self-calibrating bias correction signals. First and second inertial instruments generate respective input signals representative of an inertial attribute to be measured. A bias estimator generates first and second bias correction signals. First and second summation nodes receive the respective input signals and the respective first and second bias correction signals. The first and second summation nodes provide respective summed signals to the first and second inertial instruments. The first and second inertial instruments generate respective output signals representative of a value of the inertial attribute based on the respective summed signals. The bias estimator calculates the first and second bias correction signals based on first and second measurements made during respective first and second time intervals where a sign of one of the first and second bias error signals changes from one state during the first time interval to the other state during the second time interval.