CMOS X-ray Sensor Noise Reduction via Non-destructive Sampling
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Solution Overview
Problem
Current CMOS Active Pixel Sensors in X-ray diffraction systems face high readout noise due to thermal, 1/f noise, and dark current shot noise, which existing noise reduction techniques cannot effectively address without increasing readout dead time or failing to account for non-linear sensor responses and dynamic illumination sources.
Innovation Solution
A five-step process to reduce readout noise in CMOS Active Pixel Sensors, involving correction for gain variation and nonlinearity, estimation and subtraction of fixed pattern and dark current noise, and fitting a model function to pixel charge data using non-destructive measurements, allowing for optimal estimation of X-ray fluence while minimizing noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple non-destructive reads are performed to reduce readout noise, then readout noise is reduced by a factor of sqrt(N), but readout dead time is increased by a factor of N
Solution Approach 1:
The patent performs multiple non-destructive reads during the integration period before the final destructive read. By taking preliminary measurements of the charge at different times during integration, the system can reduce readout noise through statistical averaging while maintaining the same total readout time as a single read operation.
Solution Approach 2:
The patent dynamically samples the charge at multiple time points during the integration period rather than performing a single static read. This dynamic sampling approach allows the system to capture charge information throughout the integration window, enabling noise reduction without extending the overall measurement time.
2Measurement precision
If conventional noise reduction techniques are applied to CMOS sensors, then readout noise is reduced, but they fail to account for non-linear sensor responses and dynamic illumination sources
Solution Approach 1:
The patent changes the sampling parameters by taking multiple reads at different time points during integration. This allows the system to adapt to dynamic illumination conditions and non-linear sensor responses by capturing the charge evolution over time, thereby maintaining accuracy while reducing noise.
Solution Approach 2:
The patent uses the multiple non-destructive read measurements as feedback to model and correct for non-linear sensor behavior and dynamic illumination. By analyzing the charge values at different time points, the system can infer and compensate for non-ideal sensor characteristics, improving measurement reliability.
3Productivity
If CMOS Active Pixel Sensors are used instead of CCD detectors, then high speed readout, high quantum gain and large active areas are achieved, but readout noise is an order of magnitude larger
Solution Approach 1:
The patent performs more read operations than the minimum single read required. By executing multiple non-destructive reads during integration followed by one destructive read, the system exceeds the basic requirement and achieves noise reduction while preserving the high readout speed advantage of CMOS sensors over CCD detectors.
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
Significantly reduces readout noise in CMOS sensors while preserving speed and dynamic range, effectively addressing the limitations of prior art by accounting for non-linear sensor responses and dynamic illumination in X-ray diffraction systems.
Implementation Method 1
Each pixel of the sensor comprises a photodetector and an associated capacitor. The capacitor accumulates charge from incident X-rays during an integration time.
Data Source
Figure 1~2
Figure 3~4B
Figure 5
AI summary
Readout noise for each pixel in a CMOS Active Pixel Sensor is reduced by a five step process in which the pixel charge data from the sensor is nondestructively sampled at a plurality of times during a sensor frame time period and corrected for gain variation and nonlinearity. Then fixed pattern 5 and dark current noise is estimated and subtracted from the corrected pixel charge data. Next, reset noise is estimated and subtracted from the pixel charge data. In step four, a model function of charge versus time is fit to the corrected pixel charge data samples. Finally, the fitted model function is evaluated at frame boundary times.