Results 81 to 90 of about 12,268,087 (190)

Ground moving target indication of polarimetric interferometric synthetic aperture radar using joint scattering vector

IET Radar, Sonar &Navigation, Volume 18, Issue 12, Page 2681-2697, December 2024.
SAR GMTI is of great importance for both civlisation and military applications. The clutter suppression performance is an important assurance for the accuracy and precision of GMTI. To achieve better clutter suppression performance, it often requires extremely precise registration of multi‐channel data, including polarization and interferometric ...
Jing Xu, Long Cheng, Chunhui Yu, Shiwei Zhang   +3 more
wiley   +1 more source

Artificial Intelligence applications in Noise Radar Technology

IET Radar, Sonar &Navigation, Volume 18, Issue 7, Page 986-1001, July 2024.
Abstract Radar systems are a topic of great interest, especially due to their extensive range of applications and ability to operate in all weather conditions. Modern radars have high requirements such as its resolution, accuracy and robustness, depending on the application.
Afonso L. Sénica, Paulo A. C. Marques, Mário A. T. Figueiredo   +2 more
wiley   +1 more source

Sparse vegetation height estimation based on non‐local sample selection with generalised inner product

IET Radar, Sonar &Navigation, Volume 18, Issue 7, Page 1106-1115, July 2024.
The manuscript mainly investigates the sparse distributed vegetation height inversion problem. By analysing the scattering mechanisms of the sparse distributed vegetation, the authors proposed a method to select the samples to estimate PolInSAR coherence and vegetation height in non‐local areas by using the amplitude‐normalised interferometric phase ...
Jing Xu, Long Cheng, Chao Xue, Zhiyong Suo   +3 more
wiley   +1 more source

Assessment of Pre‐ and Post‐Fire Fuel Availability for Wildfire Management Based on L‐Band Polarimetric SAR

Earth and Space Science, Volume 11, Issue 4, April 2024.
Abstract Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post‐event assessment, offering fire agencies opportunities for additional surveillance with radar, an all‐weather instrument that can image day or night.
Karen An, Cathleen E. Jones, Yunling Lou
wiley   +1 more source

A novel self‐supervised ensemble learning framework for land use and land cover classification of polarimetric synthetic aperture radar images

IET Radar, Sonar &Navigation, Volume 18, Issue 3, Page 379-409, March 2024.
The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. Also, the designed deep learning model can obtain the effective features of homogeneous samples gathering together and heterogeneous samples separating from each other in a self‐supervised manner.
Mohsen Darvishnezhad, Mohammad Ali Sebt
wiley   +1 more source

Pearl Millet Crop Biophysical Parameter Retrieval From Space Borne Polarimetric SAR Data Using Machine Learning

Earth and Space Science, Volume 11, Issue 1, January 2024.
Abstract The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height,
Dharanya Thulasiraman, Dipanwita Haldar, Shashi Kumar, Arun Balaji Ramathilagam, N. R. Patel   +4 more
wiley   +1 more source

Context-Based Max-Margin for PolSAR Image Classification

IEEE Access, 2017
Context-based method for classification has been successfully applied in image. However, most of these classifiers work in stages. This paper presents a novel discriminative model named context-based max-margin to perform the task of classification for polarimetric synthetic aperture radar (PolSAR) images.
Shuyin Zhang, Biao Hou, Licheng Jiao, Qian Wu, Chen Sun, Wen Xie 0007   +5 more
openaire   +3 more sources

On the Interpretation of L- and P-Band PolSAR Signatures of Polythermal Glaciers [PDF]

, 2013
Long-wavelength (e.g. P- and L- band) SAR systems can penetrate tens of meters deep into ice bodies. Hence, they are sensitive to the ice surface as well as to sub-surface (volume) ice structures.
Hajnsek, Irena, Parrella, Giuseppe, Papathanassiou, Konstantinos   +2 more
core  

Global Polarimetric Synthetic Aperture Radar Image Segmentation with Data Augmentation and Hybrid Architecture Model

Remote Sensing
Machine learning and deep neural networks have shown satisfactory performance in the supervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, the PolSAR image classification task still faces some challenges. First, the
Zehua Wang, Zezhong Wang, Xiaolan Qiu, Zhe Zhang   +3 more
doaj   +1 more source

Robust Classification of PolSAR Images Based on Pinball loss Support Vector Machine

Leida xuebao, 2019
Given the problems that the amount of supervised information in the Polarimetric Synthetic Aperture Radar (PolSAR) image is low and the speckle noise is difficult to eliminate, in this study, a robust classification algorithm for PolSAR image based on ...
ZHANG Lamei, ZHANG Siyu, DONG Hongwei, ZHU Sha   +3 more
doaj   +1 more source