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Application of Linearization and Approximation01:29

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A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
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    This study introduces a new method to improve photon detection accuracy in single-photon avalanche diodes (SPADs) by addressing the pile-up effect. The advanced algorithm enhances imaging precision and noise robustness for better detection results.

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    Area of Science:

    • Photonics and Optical Engineering
    • Signal Processing
    • Computational Imaging

    Background:

    • The pile-up effect in single-photon avalanche diodes (SPADs) under high photon flux limits detection accuracy.
    • Existing recursive correction methods fail to fully utilize time-domain information, causing errors in noisy conditions.

    Purpose of the Study:

    • To develop a novel, high-precision imaging parameter inversion algorithm for SPADs.
    • To enhance noise robustness and detection accuracy, particularly under complex illumination and moderate to high noise intensity.

    Main Methods:

    • Constructed a smooth photon detection probability distribution model using Gaussian waveform priors and a Poisson response model.
    • Developed an iterative inversion algorithm incorporating adaptive moment estimation (Adam) and adaptive parameter initialization.
    • Validated the method through extensive simulations and real-system testing.

    Main Results:

    • The proposed method demonstrates superior noise robustness compared to existing algorithms.
    • Achieved a significant reduction in root mean square error (RMSE) by 5.71 cm under specific signal and noise photon counts (0.1 each).
    • Reduced RMSE from 12.766 cm to 7.056 cm in experimental conditions.

    Conclusions:

    • The novel algorithm effectively overcomes the limitations of traditional methods for SPADs.
    • The developed model and inversion technique offer a significant advancement in high-precision imaging and noise reduction for photon detection.