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Communication dans un congrès

Radar Target Recognition using Time-Frequency Analysis and Polar Transformation

Jean-Christophe Cexus 1 Abdelmalek Toumi 1
1 Lab-STICC_ENSTAB_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : A new method for Automatic Radar Targets Recognition is presented based on Inverse Synthetic Aperture Radar ISAR). In this work, the first step is to construct ISAR images via a Non uniformly Sampled Bivariate Empirical Mode Decomposition Time-Frequency Distribution (NSBEMD-TFD) method. Indeed, this Time-Frequency representation is well suited for non-stationary signals analysis and provides high resolution with good accuracy. The obtained ISAR images is used to provide the evolution of two-dimensional spatial distribution of a moving target and, therefore, its are suitable to be used for radar target recognition tasks. In second step, a feature vectors are extracted from each ISAR images in order to describe the discriminative informations about a target. In the features extraction step, we computed several rings of polar space applied on ISAR image. Then, these rings is projected on 1-D vector. To ensure translation invariance of the obtained projected 1-D vector, a Fourier Descriptors are computed. In third step of this work, the recognition task is achieved using k-Nearest Neighbors (KNN), Fuzzy k-NN, Neural network and Bayesian classifiers. To validate our approach, simulation results are presented on a set of several targets constituted by ideal point scatterers models.
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https://hal-ensta-bretagne.archives-ouvertes.fr/hal-01809365
Contributeur : Claude Morvan <>
Soumis le : mercredi 6 juin 2018 - 16:20:40
Dernière modification le : mercredi 24 juin 2020 - 16:19:52

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Jean-Christophe Cexus, Abdelmalek Toumi. Radar Target Recognition using Time-Frequency Analysis and Polar Transformation. 4th International Conference on Advanced Technologies For Signal and Image Processing (ATSIP'2018), Mar 2018, Sousse, Tunisia. ⟨10.1109/ATSIP.2018.8364500⟩. ⟨hal-01809365⟩

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