Fiber Optic Gyroscope Noise Monitoring via Digital RIN Subtraction
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Solution Overview
Problem
Angle random walk (ARW) noise in fiber optic gyros limits the accuracy of rotation measurements, degrading over time due to faults or aging, and existing methods lack effective noise reduction techniques.
Innovation Solution
A system utilizing high-speed photodiodes and analog-to-digital converters to measure noise levels, with digital relative-intensity-noise subtraction and noise monitoring locations to determine ARW, employing noise estimation techniques like RMS or peak-to-peak analysis to reduce noise and improve measurement accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise reduction techniques are implemented to reduce ARW, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary noise monitoring system that includes separate photodiodes and signal processing circuits. These intermediaries monitor the noise characteristics of the FOG without directly interfering with the primary measurement function, allowing for noise reduction through analysis and filtering while maintaining measurement accuracy.
Solution Approach 2:
The patent replaces mechanical or traditional analog noise filtering methods with digital signal processing techniques. By using digital filters and algorithms to process signals from photodiodes and ADCs, the system achieves noise reduction without the physical complexity of mechanical filters, thereby improving measurement precision while controlling device complexity.
2Reliability
If continuous monitoring is performed to detect ARW degradation, then reliability is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic monitoring of noise characteristics rather than continuous full-system analysis. By sampling noise levels at intervals and using threshold-based detection, the system maintains reliability in detecting ARW degradation while significantly reducing energy consumption compared to continuous comprehensive monitoring.
Solution Approach 2:
The system uses the FOG's own output signals and built-in photodiodes to monitor its own noise characteristics. This self-service approach allows the gyroscope to detect its own degradation without requiring external monitoring equipment, improving reliability while minimizing additional energy consumption.
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
The system effectively reduces noise in fiber optic gyros, enhancing the accuracy of angular velocity measurements by isolating and quantifying ARW, thereby mitigating navigation errors and extending the operational lifespan of the gyros.
Implementation Method 1
first and second photodiodes configured to respectively receive a first and second light signal from a light source and a fiber optic coil associated with the FOG
Implementation Method 2
A FOG uses the interference of light to measure angular velocity... two light beams are fired into the coil in opposite directions... the phase shift introduced due to the Sagnac effect causes the beams to interfere
Data Source
AI summary
A system for determining a level of angle random walk (ARW) associated with a fiber optic gyroscope (FOG) includes first and second photodiodes. The first photodiode is configured to receive a first light signal from a light source associated with the FOG. The second photodiode is configured to receive a second light signal from a fiber optic coil associated with the FOG. First and second analog-to-digital converters (ADCs) are operable to respectively convert the first and second light signals into corresponding respective first and second digital signals. A digital relative-intensity-noise (RIN) subtraction element is configured to receive the first and second digital signals and output a third signal based on the first and second digital signals. An electronic device is configured to determine a first noise level associated with the third signal, and determine the ARW level from the first noise level.