Humanitarian demining by scientific methods is a very important technical issues and ground penetrating radar (GPR) can be one of the best solutions for this difficult task. However, strong clutter makes difficult for detecting buried landmines in real situations. We have developed a synthetic aperture based GPR and tested its capabilities by experiments. We found that synthetic aperture radar ...

The 2 workshop on Coastal and Marine Applications of Synthetic Aperture Radar was held in Svalbard Norway on 8-12 September 2003. This conference was focused on providing an overview of the tools now available within the international community for utilizing synthetic aperture radar (SAR) systems to characterize the marine environment. Applications were specifically focused on wind, waves, sea ...

Recognition of occluded objects in synthetic aperture radar SAR images is a signi cant problem for automatic target recognition Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise In this paper we present a discrete hidden Markov modeling HMM based approach for recognizing objects in synthetic aperture radar SAR images We ide...

This paper presents a comparison study on the application of two electromagnetic inverse scattering algorithms, SEABED [1] and the synthetic aperture method, to experimental multi-static UWB (Ultra Wide-Band) radar data. A linear UWB antenna array with a wideband frequency (1.5-8 GHz) was used for the multi-static radar measurement in a realistic environment. The results clearly show the advant...

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. SAR technology, due to its high spatial resolution and soil penetration capability, is a good choice to identify problematic areas on earthen levees. In this paper, using the entropy (H), alpha angle ( ), and eigenvalue parameters (λ), we implemented several unsu...

We propose a novel approach for generating high quality visible-like images from Synthetic Aperture Radar (SAR) images using Deep Convolutional Generative Adversarial Network (GAN) architectures. The proposed approach is based on a cascaded network of convolutional neural nets (CNNs) for despeckling and image colorization. The cascaded structure results in faster convergence during training and...

We present an overview of independent component analysis, an emerging signal processing technique based on neural networks, with the aim to provide an up-to-date survey of the theoretical streams in this discipline and of the current applications in the engineering area. We also focus on a particular application, dealing with a remote sensing technique based on synthetic aperture radar imagery ...

This study concerned with fusion of synthetic aperture radar and optical satellite imagery. Due to the difference in the underlying sensor technology, data from synthetic aperture radar (SAR) and optical sensors refer to different properties of the observed scene and it is believed that when they are fused together, they complement each other to improve the performance of a particular applicati...

Most paddy rice in the world grows in warm, humid and rainy environment where it is hard to acquire optical remote sensing data. Synthetic Aperture Radar (SAR) can acquire remote sensing information due to its all weather imaging and frequent revisit capability in the areas. A semi-empirical backscattering model was used to estimate leaf area index (LAI) from ENVISAT ASAR (Advanced Synthetic Ap...

Improved radio frequency interference suppression method based on short time Fourier transform applied to synthetic aperture radar is proposed in this paper. The radio frequency interference, including narrow-band interference and wide-band interference, are analyzed in time frequency domain. The interference is identified at instantaneous frequency spectrum by a novel threshold criterion in ti...