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Related Concept Videos

Distance Corrections01:15

Distance Corrections

62
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Influence of Earth's Curvature and Atmospheric Refraction on Leveling01:26

Influence of Earth's Curvature and Atmospheric Refraction on Leveling

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During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance.
221

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Related Experiment Video

Updated: Aug 25, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
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Deviation-based wavefront correction using the SPGD algorithm for high-resolution optical remote sensing.

Makoto Hirose, Norihide Miyamura, Seichi Sato

    Applied Optics
    |October 18, 2022
    PubMed
    Summary
    This summary is machine-generated.

    Image-based wavefront correction using the stochastic parallel gradient descent (SPGD) algorithm is key for remote sensing. A deviation-based cost function improves correction speed and performance across diverse scenes.

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    Area of Science:

    • Optical remote sensing
    • Adaptive optics
    • Image processing

    Background:

    • Achieving diffraction-limited optical performance is crucial for advanced remote sensing systems.
    • Model-free image-based wavefront correction methods, like the stochastic parallel gradient descent (SPGD) algorithm, face challenges related to performance dependency on evaluation metrics and scene characteristics.

    Purpose of the Study:

    • To investigate the relationship between optimization speed and scene textures for various evaluation metrics within the SPGD algorithm.
    • To identify optimal evaluation functions for efficient wavefront correction in optical remote sensing.

    Main Methods:

    • Proposed and evaluated several image-based cost functions for wavefront correction.
    • Utilized the stochastic parallel gradient descent (SPGD) algorithm for optimization.
    • Conducted simulations and experimental comparisons using four cost functions and two extended aerial images.
    • Validated the approach in a segmented-aperture imaging system for large telescopes.

    Main Results:

    • The deviation-based cost function demonstrated efficient wavefront correction for versatile extended scenes.
    • Distinct structures within extended scenes were found to facilitate faster correction speeds.
    • Numerical validation in a segmented-aperture system confirmed the approach's effectiveness.

    Conclusions:

    • The deviation-based cost function is highly effective for wavefront correction in diverse remote sensing scenarios.
    • Scene characteristics, particularly distinct structures, significantly impact correction speed.
    • This approach enables high angular resolution in spaceborne remote sensing applications.