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A Kriging-based Interacting Particle Kalman Filter for the simultaneous estimation of temperature and emissivity in Infra-Red imaging

Thibaud Toullier 1 Jean Dumoulin 2, 1 Laurent Mevel 1, 2
1 I4S - Statistical Inference for Structural Health Monitoring
Inria Rennes – Bretagne Atlantique , COSYS - Département Composants et Systèmes
Abstract : Temperature estimation through infrared thermography is facing the lack of knowledge of the observed material's emissivity. The derivation of the physical equations lead to an ill-posed problem. A new Kriged Interacting Particle Kalman Filter is proposed. A state space model relates the measurements to the temperature and the Kalman filter equations yield a filter tracking the temperature over time. Moreover, a particle filter associated to Kriging prediction is interacting with a bank of Kalman filters to estimate the time-varying parameters of the system. The efficiency of the algorithm is tested on a simulated sequence of infrared thermal images.
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https://hal.inria.fr/hal-02940184
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Submitted on : Wednesday, September 16, 2020 - 10:24:05 AM
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Thibaud Toullier, Jean Dumoulin, Laurent Mevel. A Kriging-based Interacting Particle Kalman Filter for the simultaneous estimation of temperature and emissivity in Infra-Red imaging. IFAC 2020 – 21st IFAC World Congress, Jul 2020, Berlin, Germany. ⟨hal-02940184⟩

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