研究目的
Investigating the parameters of a high dynamic range (HDR) image sensor with LED flicker mitigation (LFM) operating in automotive temperature range, focusing on SNR improvement through FD DC and DSNU reduction, and analyzing temperature dependencies of QE, sensitivity, and color effects.
研究成果
The 3.0 μm 2.6M pixels HDR LFM image sensor effectively operates in the automotive temperature range, providing high dynamic range and SNR suitable for small object recognition. Process optimizations led to a 28x reduction in FD DC and DSNU, improving SNR at high temperatures. Temperature dependencies of QE and sensitivity were characterized, showing minimal impact on visual range performance but significant improvements in NIR sensitivity. Color accuracy was maintained with slight tints at high temperatures, manageable through auto white balancing and color correction.
研究不足
The study is limited by the specific process conditions of the three wafer fabs, which may not be universally applicable. The impact of high temperatures on color accuracy, while minimal, may require further optimization for certain applications. The study also notes the need for more research into the effects of water boiling temperature on QE and sensitivity.
1：Experimental Design and Method Selection
The study involves the design and testing of a 3.0 μm 2.6M pixels HDR LFM CMOS image sensor with backside illumination (BSI) technology. The methodology includes TCAD simulations for process optimization, Monte Carlo simulations for LED detection probability and signal fluctuation analysis, and experimental measurements of sensor parameters across a wide temperature range.
2：Sample Selection and Data Sources
Samples include sensors fabricated in three different wafer fabs with varying process conditions. Data sources include QE measurements from 390 to 1100 nm, sensitivity measurements under D65 and A-light spectra, and color accuracy assessments using Macbeth chart images.
3：List of Experimental Equipment and Materials
Monochromator setup with a 5 nm grating and a NIST calibrated photodiode for QE measurements, TCAD tools for process simulation, and image capture setups for color accuracy and SNR assessments.
4：Experimental Procedures and Operational Workflow
The workflow includes process optimization through TCAD simulations, fabrication of sensor samples, QE and sensitivity measurements across temperatures, and image quality assessments under various lighting conditions.
5：Data Analysis Methods
Data analysis involves comparing measured QE and sensitivity changes across temperatures, assessing SNR improvements from process modifications, and evaluating color accuracy impacts through image analysis.
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