scholarly journals How to Obtain a SAR Image of the Ocean Surface That Is Actually Free from The Impact of Orbital Velocities

2021 ◽  
Vol 4 (2) ◽  
Keyword(s):  
Synthetic Aperture Radar ◽  
Ocean Surface ◽  
Synthetic Aperture ◽  
Small Scale ◽  
Matched Filtering ◽  
Sar Image ◽  
Synthesis Procedure ◽  
Reflected Signal ◽  
Reflecting Surface ◽  
The Impact

As is known, the main problem in interpreting images of the ocean surface formed by microwave synthetic aperture radar (SAR) is the distortions introduced by the orbital movements of the small-scale (centimeter and decimeter) ripples in the field of large waves. The point is that the standard aperture synthesis procedure is a matched filtering operation aimed at extracting from the reflected signal a part that has a phase that changes according to a known scenario corresponding to a stationary reflecting surface.

scholarly journals Measurement of turbulence in the oceanic mixed layer using Synthetic Aperture Radar (SAR)

2012 ◽  
Vol 9 (5) ◽  
pp. 2851-2883 ◽  
Author(s):  
S. G. George ◽  
A. R. L. Tatnall
Keyword(s):  
Surface Layer ◽  
Synthetic Aperture Radar ◽  
Wave Interaction ◽  
Surface Current ◽  
Surface Flow ◽  
Synthetic Aperture ◽  
Small Scale ◽  
Radar Images ◽  
The Impact ◽  
Aperture Radar

Abstract. Turbulence in the surface layer of the ocean contributes to the transfer of heat, gas and momentum across the air-sea boundary. As such, study of turbulence in the ocean surface layer is becoming increasingly important for understanding its effects on climate change. Direct Numerical Simulation (DNS) techniques were implemented to examine the interaction of small-scale wake turbulence in the upper ocean layer with incident electromagnetic radar waves. Hydrodynamic-electromagnetic wave interaction models were invoked to demonstrate the ability of Synthetic Aperture Radar (SAR) to observe and characterise surface turbulent wake flows. A range of simulated radar images are presented for a turbulent surface current field behind a moving surface vessel, and compared with the surface flow fields to investigate the impact of turbulent currents on simulated radar backscatter. This has yielded insights into the feasibility of resolving small-scale turbulence with remote-sensing radar and highlights the potential for extracting details of the flow structure and characteristics of turbulence using SAR.

scholarly journals Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 396 ◽  
Author(s):  
Peng Wang ◽  
Cheng Xing ◽  
Xiandong Pan
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Small Scale ◽  
Sar Image ◽  
Large Reservoir ◽  
Deformation State ◽  
Before And After ◽  
Aperture Radar

Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.

scholarly journals Realizing Target Detection in SAR Images Based on Multiscale Superpixel Fusion

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1643
Author(s):  
Ming Liu ◽  
Shichao Chen ◽  
Fugang Lu ◽  
Mengdao Xing ◽  
Jingbiao Wei
Keyword(s):  
Synthetic Aperture Radar ◽  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Synthetic Aperture ◽  
False Alarms ◽  
Sar Image ◽  
Constant False Alarm Rate ◽  
Sar Images ◽  
Complex Scenes

For target detection in complex scenes of synthetic aperture radar (SAR) images, the false alarms in the land areas are hard to eliminate, especially for the ones near the coastline. Focusing on the problem, an algorithm based on the fusion of multiscale superpixel segmentations is proposed in this paper. Firstly, the SAR images are partitioned by using different scales of superpixel segmentation. For the superpixels in each scale, the land-sea segmentation is achieved by judging their statistical properties. Then, the land-sea segmentation results obtained in each scale are combined with the result of the constant false alarm rate (CFAR) detector to eliminate the false alarms located on the land areas of the SAR image. In the end, to enhance the robustness of the proposed algorithm, the detection results obtained in different scales are fused together to realize the final target detection. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

scholarly journals COSMO–SkyMed Synthetic Aperture Radar Data to Observe the Deepwater Horizon Oil Spill

2018 ◽  
Author(s):  
Ferdinando Nunziata ◽  
Andrea Buono ◽  
Maurizio Migliaccio
Keyword(s):  
Synthetic Aperture Radar ◽  
Oil Spills ◽  
Oil Pollution ◽  
Deepwater Horizon ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Pollution Event ◽  
The Impact ◽  
Csk Constellation ◽  
Aperture Radar

Oil spills are adverse events that may be very harmful to ecosystems and food chain. In particular, large sea oil spills are very dramatic occurrence often affecting sea and coastal areas. Therefore the sustainability of oil rig infrastructures and oil transportation via oil tankers are linked to law enforcement based on proper monitoring techniques which are also fundamental to mitigate the impact of such pollution. Within this context, in this study a meaningful showcase is analyzed using remotely sensed measurements collected by the Synthetic Aperture Radar (SAR) operated by the COSMO-SkyMed (CSK) constellation. The showcase presented refers to the Deepwater Horizon (DWH) oil incident that occurred in the Gulf of Mexico in 2010. It is one of the world's largest incidental oil pollution event that affected a sea area larger than 10,000 km2. In this study we exploit, for the first time, dual co-polarization SAR data collected by the Italian CSK X-band SAR constellation showing the key benefits of HH-VV SAR measurements in observing such a huge oil pollution event, especially in terms of the very dense revisit time offered by the CSK constellation.

scholarly journals Micro-Motion Estimation of Maritime Targets Using Pixel Tracking in Cosmo-Skymed Synthetic Aperture Radar Data—An Operative Assessment

2019 ◽  
Vol 11 (14) ◽  
pp. 1637 ◽  
Author(s):  
Filippo Biondi ◽  
Pia Addabbo ◽  
Danilo Orlando ◽  
Carmine Clemente
Keyword(s):  
Synthetic Aperture Radar ◽  
Wide Band ◽  
Radar Data ◽  
Satellite System ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Synthetic Aperture Radar Data ◽  
Micro Motion ◽  
Novel Strategy ◽  
Aperture Radar

In this paper, we propose a novel strategy to estimate the micro-motion (m-m) of ships from synthetic aperture radar (SAR) images. To this end, observe that the problem of motion and m-m detection of targets is usually solved using synthetic aperture radar (SAR) along-track interferometry through two radars spatially separated by a baseline along the azimuth direction. The approach proposed in this paper for m-m estimation of ships, occupying thousands of pixels, processes the information generated during the coregistration of several re-synthesized time-domain and not overlapped Doppler sub-apertures. Specifically, the SAR products are generated by splitting the raw data according to a temporally small baseline using one single wide-band staring spotlight (ST) SAR image. The predominant vibrational modes of different ships are then estimated. The performance analysis is conducted on one ST SAR image recorded by COSMO-SkyMed satellite system. Finally, the newly proposed approach paves the way for application to the surveillance of land-based industry activities.

Speckle Noise Filtering Using Back-Propagation Multi-Layer Perceptron Network in Synthetic Aperture Radar Image

2020 ◽  
pp. 489-510
Author(s):  
Khwairakpam Amitab ◽  
Debdatta Kandar ◽  
Arnab K. Maji
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Synthetic Aperture Radar ◽  
Back Propagation ◽  
Speckle Noise ◽  
Synthetic Aperture ◽  
Sar Image ◽  
Multi Layer Perceptron ◽  
Sar Images ◽  
Artificial Neural

Synthetic Aperture Radar (SAR) are imaging Radar, it uses electromagnetic radiation to illuminate the scanned surface and produce high resolution images in all-weather condition, day and night. Interference of signals causes noise and degrades the quality of the image, it causes serious difficulty in analyzing the images. Speckle is multiplicative noise that inherently exist in SAR images. Artificial Neural Network (ANN) have the capability of learning and is gaining popularity in SAR image processing. Multi-Layer Perceptron (MLP) is a feed forward artificial neural network model that consists of an input layer, several hidden layers, and an output layer. We have simulated MLP with two hidden layer in Matlab. Speckle noises were added to the target SAR image and applied MLP for speckle noise reduction. It is found that speckle noise in SAR images can be reduced by using MLP. We have considered Log-sigmoid, Tan-Sigmoid and Linear Transfer Function for the hidden layers. The MLP network are trained using Gradient descent with momentum back propagation, Resilient back propagation and Levenberg-Marquardt back propagation and comparatively evaluated the performance.

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