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Design rules for Unipolar Unicolor Coded Brillouin Optical Time Domain Analysis

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Luc Thévenaz, Zhisheng Yang, Marcelo Alfonso Soto Hernandez, Simon Adrien Zaslawski, Zonglei Li
2018

Abstract

The performance of unipolar unicolor coded Brillouin optical time-domain analysis (BOTDA) is thoroughly studied, providing quantitative guidelines to design a distortion-free coded BOTDA system operating at maximum signal-to-noise ratio.

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https://infoscience.epfl.ch/entities/publication/cd060512-c327-409e-9560-ec4b439fff7f

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Related concepts (6)

Signal-to-noise ratio

Signal-to-noise ratio (SNR or S/N) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. SNR is defined as the ratio of signal power to noise power, often expressed in decibels. A ratio higher than 1:1 (greater than 0 dB) indicates more signal than noise. SNR is an important parameter that affects the performance and quality of systems that process or transmit signals, such as communication systems, audio systems, radar systems, imaging systems, and data acquisition systems.

Noise (signal processing)

In signal processing, noise is a general term for unwanted (and, in general, unknown) modifications that a signal may suffer during capture, storage, transmission, processing, or conversion. Sometimes the word is also used to mean signals that are random (unpredictable) and carry no useful information; even if they are not interfering with other signals or may have been introduced intentionally, as in comfort noise. Noise reduction, the recovery of the original signal from the noise-corrupted one, is a very common goal in the design of signal processing systems, especially filters.

Quantization (signal processing)

Quantization, in mathematics and digital signal processing, is the process of mapping input values from a large set (often a continuous set) to output values in a (countable) smaller set, often with a finite number of elements. Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing, as the process of representing a signal in digital form ordinarily involves rounding. Quantization also forms the core of essentially all lossy compression algorithms.

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