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Mathematical Model and Synthetic Data Generation for Infra-Red Sensors

  • Laura Leja
  • , Vitālijs Purlans
  • , Rihards Novickis
  • , Rihards Novickis
  • , Cvetkovs Andrejs
  • , Jānis Cvetkovs
  • , Kaspars Ozols
  • , Kaspars Ozols
    • Ne LU

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    Abstract

    A key challenge in further improving infrared (IR) sensor capabilities is the development of efficient data pre-processing algorithms. This paper addresses this challenge by providing a mathematical model and synthetic data generation framework for an uncooled IR sensor. The developed model is capable of generating synthetic data for the design of data pre-processing algorithms of uncooled IR sensors. The mathematical model accounts for the physical characteristics of the focal plane array, bolometer readout, optics and the environment. The framework permits the sensor simulation with a range of sensor configurations, pixel defectiveness, non-uniformity and noise parameters.

    Original languageEnglish
    Article number9458
    Pages (from-to)1-15
    JournalSensors
    Volume22
    Issue number23
    DOIs
    Publication statusPublished - Dec 2022

    OECD Field of Science

    • 1.1 Mathematics

    Keywords

    • calibration
    • infrared sensors
    • microbolometer
    • non-uniformity
    • synthetic data

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