Speckle Prediction for SMI Sensor Power Optimization
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Solution Overview
Problem
Coherent optical sensing systems, such as self-mixing interferometry (SMI) sensors, face performance and accuracy issues due to speckle interference, which causes random modulation of the SMI signal and phase errors, leading to periods where the signal fades below the noise floor or saturates, affecting the reliability and power efficiency of physical phenomenon measurements.
Innovation Solution
The system predicts interference caused by speckle in the SMI signal and adjusts the emission characteristics of the electromagnetic radiation, such as power and waveform, and sampling parameters, based on this prediction to minimize interference impact and optimize power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If continuous emission of electromagnetic radiation is used for SMI sensing, then measurement coverage is improved, but power consumption increases and speckle interference cannot be avoided
Solution Approach 1:
The system uses periodic pulsed emission of electromagnetic radiation instead of continuous emission. The controller activates the SMI sensor to emit radiation in periodic intervals, allowing measurement coverage to be maintained while significantly reducing power consumption during periods when emission is not required.
Solution Approach 2:
The system performs preliminary prediction of speckle interference patterns using historical SMI signal data and speckle prediction models. This preliminary action allows the controller to anticipate periods of high interference and adjust emission timing accordingly, optimizing both measurement coverage and power efficiency.
2Measurement precision
If continuous sampling of SMI signal is performed, then measurement accuracy is improved, but power consumption increases
Solution Approach 1:
The system implements periodic sampling of the SMI signal rather than continuous sampling. The controller determines optimal sampling intervals based on predicted speckle interference patterns, maintaining measurement accuracy during low-interference periods while reducing power consumption by excluding sampling during predicted high-interference periods.
Solution Approach 2:
The system uses feedback from historical SMI signal analysis and speckle prediction models to dynamically adjust sampling rates. The controller continuously monitors signal quality metrics and adapts sampling frequency to maintain measurement accuracy while optimizing power consumption based on real-time interference conditions.
3Productivity
If SMI sensor operates during periods of speckle interference, then data collection is continuous, but measurement reliability deteriorates
Solution Approach 1:
The system performs preliminary prediction of speckle interference using historical signal analysis and speckle models before data collection. This allows the controller to identify and avoid periods of high interference, ensuring measurement reliability is maintained while minimizing gaps in data collection during low-interference windows.
Solution Approach 2:
The system converts the harmful effect of speckle interference into a useful predictive signal. By analyzing speckle patterns in historical data, the system develops prediction models that identify interference periods, allowing the controller to strategically avoid these periods and improve overall measurement reliability while maintaining productive data collection during favorable conditions.
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 improves the accuracy and reliability of physical phenomenon measurements by reducing the impact of speckle interference and minimizing power consumption during periods of interference, thereby enhancing the overall performance and battery life of electronic devices.
Implementation Method 1
coherent optical sensing such as self-mixing interferometry (SMI)... generating, by an SMI sensor, an SMI signal... the SMI signal is based at least in part on reflections of the emitted electromagnetic radiation
Implementation Method 2
predicting interference in the SMI signal caused by speckle... speckle interference, which causes random modulation of the SMI signal and phase errors
Data Source
AI summary
An electronic device including an SMI sensor may be operated to predict interference in an SMI signal caused by speckle provided by the SMI sensor and operate the SMI sensor based on predicted interference in the SMI signal caused by speckle. Predicting interference in the SMI signal caused by speckle and operating the SMI sensor accordingly may allow for accurate measurement of physical phenomena using the SMI sensor with reduced power consumption.