Calibration of a Radar Cross-section Model using a Surrogate Model Optimization Algorithm - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Calibration of a Radar Cross-section Model using a Surrogate Model Optimization Algorithm

Calibrage d'un modèle de section efficace radar en utilisant un algorithme d'optimisation de modèle substitut

Résumé

EMPRISE® is a software package under developmentused by sensor and radar system companies, as well as the French government for its equipment programs. The software simulates the IQ signals received by a radar system from the digital twin of a radar scene. The goal of any simulation software, such as EMPRISE®, is to quantify the performance of a given radar system in a given environment. To improve the software representativeness of these simulators, it is necessary to calibrate the radar material cross-sections used by the scene model according to measurement data. In this paper, we propose a calibration method, applied to EMPRISE®, based on an adaptive surrogate model and a minimizing search algorithm.

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Dates et versions

hal-04427159 , version 1 (30-01-2024)

Identifiants

  • HAL Id : hal-04427159 , version 1

Citer

Thomas Houret, Olivier Lévêque, Nicolas Trouvé, Romain Bocheux, Xavier Husson, et al.. Calibration of a Radar Cross-section Model using a Surrogate Model Optimization Algorithm. IEEE Radar Conference 2023, Nov 2023, Sydney, Australia. ⟨hal-04427159⟩
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