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Related Concept Videos

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

594
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
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Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

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The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
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Updated: Oct 17, 2025

Direct Comparison of Hyperspectral Stimulated Raman Scattering and Coherent Anti-Stokes Raman Scattering Microscopy for Chemical Imaging
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Detection statistics for coherent RMCW LiDAR.

Callum S Sambridge, James T Spollard, Andrew J Sutton

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    |October 7, 2021
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    Summary
    This summary is machine-generated.

    This study models detection performance for phase-encoded random modulation continuous-wave (RMCW) LiDAR. Performance depends on signal-to-noise ratio (SNR), integration time, and speckle noise, validated experimentally.

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    Area of Science:

    • Optics and Photonics
    • Remote Sensing
    • Signal Processing

    Background:

    • Continuous-wave (CW) LiDAR systems are crucial for various applications.
    • Phase-encoded Random Modulation Continuous-Wave (RMCW) LiDAR offers unique advantages.
    • Understanding detection performance and false-alarm rates is essential for RMCW LiDAR reliability.

    Purpose of the Study:

    • To develop an analytical model for RMCW LiDAR detection performance.
    • To determine the key factors influencing detection probability and false-alarm rates.
    • To validate the model through simulations and experimental measurements.

    Main Methods:

    • Analytical derivation of a detection model considering noise sources.
    • Formulation of detection probability based on signal-to-noise ratio (SNR), integration time, and speckle noise.
    • Experimental validation using controlled fiber and uncontrolled free-space channels.

    Main Results:

    • The analytical model accurately predicts detection probability.
    • Detection probability is shown to be dependent on SNR, integration time, and speckle noise.
    • Experimental results confirm the model's predictions under various conditions.

    Conclusions:

    • The developed analytical model provides a robust framework for RMCW LiDAR performance analysis.
    • The findings highlight the critical impact of SNR, integration time, and speckle noise on detection.
    • The validated model aids in optimizing RMCW LiDAR system design and deployment.