78 research outputs found
Identità sociale, identità di luogo e dilemmi ambientali: il caso delle aree naturali protette
No full textLa gestione delle risorse naturali come dilemmi sociali: una rassegna sui principali contributi di ricerca
No full textCompressive sensing for passive ISAR with DVB-T signal
No full textAs recently demonstrated, ISAR images can be obtained by using DVB-T based Passive radars. Television broadcast sources offer, however, very poor range resolution for imaging purposes, as illuminators of opportunity(IOs) transmits signals with lower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, a signal composed of multiple DVB-T channels is required. Problems arise however, when the DVB-T channels are spectrally separated. The gaps between DVB-T channels may degrade the image significantly when Fourier based algorithms are used to form the ISAR image. In this paper, the Compressive Sensing (CS) theory is investigated to address this problem. Specifically, a 2D-SL0 algorithm is used to solve a sparsity-driven optimization problem. Simulation based results are then used to validate the proposed algorithm.W Qiu, E Giusti, A Bacci, M Martorella, F Berizzi, H Z Zhao, Q F
Local conflicts and common resources use in protected areas: applying the "Social Dilemma" paradigm to biodiversity conservation
No full text
Gruppi sociali e percezione ambientale: relazioni tra identità locale, attaccamento al luogo e atteggiamenti pro-ambientali nel parco nazionale dell’arcipelago toscano
No full textLocal identity processes and environmental attitudes in land use changes: the case of natural protected areas
No full textCNN for Radial Velocity and Range Components Estimation of Ground Moving Targets in SAR
No full textGround-moving objects in synthetic aperture radar (SAR) images appear defocused and azimuthally displaced using conventional SAR image formation algorithms. In this paper, a novel regression method based on convolutional neural networks (CNNs) for the estimation of radial velocity and slant range components of ground moving targets is proposed. Motion parameters estimation can be helpful for designing additional matched filters to focus and relocate moving targets. We have generated the training and the test data in such a way that each image is indeed a 2D data matrix of a moving target. In other words, each complex image contains the range-compressed signal of only one moving target with a specified pair of (range, radial velocity). To further decrease the estimation error, we employed transfer learning by fine-tuning the pretrained AlexNet architecture in a regression problem. To verify the effectiveness of the proposed method, simulations have been performed. The results demonstrate the effectiveness of the proposed method
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