4.6 Article

Mathematical Model and Synthetic Data Generation for Infra-Red Sensors

Journal

SENSORS
Volume 22, Issue 23, Pages -

Publisher

MDPI
DOI: 10.3390/s22239458

Keywords

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

Funding

  1. APPLAUSE project - ECSEL Joint Undertaking (JU) [826588]
  2. European Union's Horizon 2020 research and innovation programme
  3. Belgium, Germany, Netherlands, Finland, Austria, France, Hungary
  4. Latvia, Norway, Switzerland and Israel

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This paper presents a mathematical model and synthetic data generation framework for uncooled infrared (IR) sensors, which addresses the challenge of improving the capabilities of IR sensors through efficient data pre-processing algorithms.
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.

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