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Variational bayesian compressive multipolarization indoor radar imaging / Van Ha Tang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7459 - 7474 Titre : Variational bayesian compressive multipolarization indoor radar imaging Type de document : Article/Communication Auteurs : Van Ha Tang, Auteur ; Abdesselam Bouzerdoum, Auteur ; Son Lam Phung, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7459 - 7474 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] acquisition comprimée [Termes IGN] détection à travers-le-mur [Termes IGN] estimation bayesienne [Termes IGN] fouillis d'échos [Termes IGN] image radar [Termes IGN] inférence statistique [Termes IGN] modèle stochastique [Termes IGN] polarisation [Termes IGN] positionnement en intérieur [Termes IGN] reconstruction d'image Résumé : (auteur) This article introduces a probabilistic Bayesian model for addressing the problem of compressive multipolarization through-wall radar imaging (TWRI). The proposed approach formulates the task of wall-clutter mitigation and multipolarization image reconstruction as a Bayesian inference problem for a joint distribution between observed radar measurements and latent wall-clutter matrix and indoor target images. The joint probability distribution incorporates three prior beliefs: low-dimensional structure of the wall reflections, group sparsity structure of the target images, and joint sparsity among the polarization images. These signal attributes are modeled through hierarchical priors, whose parameters and hyperparameters are treated with a full Bayesian formulation. Furthermore, this article presents a variational Bayesian inference algorithm that estimates wall-clutter and multipolarization images as posterior distributions and optimizes the model parameters and hyperparameters simultaneously. Experimental results on simulated and real radar data show that the proposed model is very effective at removing wall clutter and enhancing target localization even when the radar measurements are significantly reduced. Numéro de notice : A2021-647 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3051955 Date de publication en ligne : 26/01/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3051955 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98354 [article]

Image-domain estimation of wall parameters for autofocusing of through-the-wall SAR imagery / Tian Jin in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 2 (March 2013) . - pp 1836 - 1843 Titre : Image-domain estimation of wall parameters for autofocusing of through-the-wall SAR imagery Type de document : Article/Communication Auteurs : Tian Jin, Auteur ; Bo Chen, Auteur ; Zhimin Zhou, Auteur Année de publication : 2013 Article en page(s) : pp 1836 - 1843 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] constante diélectrique [Termes IGN] détection à travers-le-mur [Termes IGN] écho radar [Termes IGN] épaisseur [Termes IGN] image radar moirée [Termes IGN] milieu urbain Résumé : (Auteur) Estimation of the basic parameters, wall thickness and dielectric constant, is important in through-the-wall radar imaging. Ambiguities in wall characteristics will degrade the image focusing quality of synthetic-aperture radar. In order to obtain a quick and precise estimation of wall parameters, an equivalent propagation model of an electromagnetic wave in the air-wall-air medium is first developed in this paper. According to the developed propagation model, two filter-based approaches, denoted respectively as the echo-domain-filter-based method and the image-domain-filter-based method, are proposed to estimate wall thickness and dielectric constant by adjusting the two corresponding parameters of the echo-domain filter or the image-domain filter to obtain the best focusing quality of behind-the-wall targets. The processing schemes of the two methods show that the image-domain-filter-based method is more efficient because it does not involve imaging processing in each adjustment. Moreover, the image-domain-filter-based method is accelerated by reducing the dimension of searching space to better the computational efficiency further. Simulation results show that the proposed accelerating image-domain-filter-based method can provide quick and precise estimation of wall parameters. Numéro de notice : A2013-136 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2206395 En ligne : https://doi.org/10.1109/TGRS.2012.2206395 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32274 [article]

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Joint wall mitigation and compressive sensing for indoor image reconstruction / E. Lagunas in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 2 (February 2013) . - pp 891 - 906 Titre : Joint wall mitigation and compressive sensing for indoor image reconstruction Type de document : Article/Communication Auteurs : E. Lagunas, Auteur ; M. Armin, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 891 - 906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] acquisition comprimée [Termes IGN] carte d'intérieur [Termes IGN] détection à travers-le-mur [Termes IGN] fouillis d'échos [Termes IGN] image radar [Termes IGN] objet mobile [Termes IGN] positionnement en intérieur [Termes IGN] reconstruction d'image Résumé : (Auteur) Compressive sensing (CS) for urban operations and through-the-wall radar imaging has been shown to be successful in fast data acquisition and moving target localizations. The research in this area thus far has assumed effective removal of wall electromagnetic backscatterings prior to CS application. Wall clutter mitigation can be achieved using full data volume which is, however, in contradiction with the underlying premise of CS. In this paper, we enable joint wall clutter mitigation and CS application using a reduced set of spatial-frequency observations in stepped frequency radar platforms. Specifically, we demonstrate that wall mitigation techniques, such as spatial filtering and subspace projection, can proceed using fewer measurements. We consider both cases of having the same reduced set of frequencies at each of the available antenna locations and also when different frequency measurements are employed at different antenna locations. The latter casts a more challenging problem, as it is not amenable to wall removal using direct implementation of filtering or projection techniques. In this case, we apply CS at each antenna individually to recover the corresponding range profile and estimate the scene response at all frequencies. In applying CS, we use prior knowledge of the wall standoff distance to speed up the convergence of the orthogonal matching pursuit for sparse data reconstruction. Real data are used for validation of the proposed approach. Numéro de notice : A2013-084 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2203824 En ligne : https://doi.org/10.1109/TGRS.2012.2203824 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32222 [article]

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Through-the-wall human motion indication using sparsity-driven change detection / F. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 2 (February 2013) . - pp 881 - 890 Titre : Through-the-wall human motion indication using sparsity-driven change detection Type de document : Article/Communication Auteurs : F. Ahmad, Auteur ; M. Amin, Auteur Année de publication : 2013 Article en page(s) : pp 881 - 890 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] détection à travers-le-mur [Termes IGN] détection de changement [Termes IGN] filtrage du signal [Termes IGN] fouillis d'échos [Termes IGN] image radar [Termes IGN] objet mobile [Termes IGN] positionnement en intérieur [Termes IGN] reconstruction d'image Résumé : (Auteur) We consider sparsity-driven change detection (CD) for human motion indication in through-the-wall radar imaging and urban sensing applications. Stationary targets and clutter are removed via CD, which converts a populated scene into a sparse scene of a few human targets moving inside enclosed structures and behind walls. We establish appropriate CD models for various possible human motions, ranging from translational motions to sudden short movements of the limbs, head, and/or torso. These models permit scene reconstruction within the compressive sensing framework. Results based on laboratory experiments show that a sizable reduction in the data volume is achieved using the proposed approach without a degradation in system performance. Numéro de notice : A2013-083 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2203310 En ligne : https://doi.org/10.1109/TGRS.2012.2203310 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32221 [article]

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