scholarly journals Parasitic Surveillance Potentialities Based on a GEO-SAR Illuminator

2021 ◽  
Vol 13 (23) ◽  
pp. 4817
Author(s):  
Fabrizio Santi ◽  
Giovanni Paolo Blasone ◽  
Debora Pastina ◽  
Fabiola Colone ◽  
Pierfrancesco Lombardo
Keyword(s):  
Remote Sensing ◽  
Regional Scale ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Signal Source ◽  
Maritime Surveillance ◽  
Radar Systems ◽  
The Earth ◽  
Different Types ◽  
Wide Availability

Synthetic aperture radar systems operating with satellites in geosynchronous orbits (GEO-SAR) can provide a permanent coverage of wide specific areas of the Earth’s surface. As well as for primary applications in remote sensing areas such as soil moisture and deformation monitoring, the wide availability of the signal emitted by a GEO-SAR on a regional scale makes it an appealing illuminator of opportunity for bistatic radars. Different types of receiving-only devices located on or near the Earth could exploit the same signal source, noticeably already conceived for radar purposes, for applications in the framework of both military and civil surveillance. This paper provides an overview of possible parasitic applications enabled by a GEO-SAR illuminator in different operative scenarios, including aerial, ground and maritime surveillance. For each selected scenario, different receiver configurations are proposed, providing an assessment of the achievable performance with discussions about the expected potentialities and challenges. This research aims at serving as a roadmap for designing parasitic systems relying on GEO-SAR signals, and also aims at extending the net of potential users interested in investing in GEO-SAR missions.

Deformation information extraction method based on differential synthetic aperture radar interferometry

2020 ◽  
Vol 39 (4) ◽  
pp. 5311-5318
Author(s):  
Zhengquan Hu ◽  
Yu Liu ◽  
Xiaowei Niu ◽  
Guoping Lei
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Adaptive Filtering ◽  
Extraction Method ◽  
Deformation Monitoring ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Filtering Method ◽  
Synthetic Aperture Radar Interferometry ◽  
Aperture Radar

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.

scholarly journals KNOWLEDGE BASED CLASSIFIER BASED ON BACKSCATTERING COEFFICIENT FOR MONITORING THE CROP GROWTH ANALYSIS USING MULTI-TEMPORAL IMAGES OF SPACE-BORNE SYNTHETIC APERTURE RADAR (SAR) SENSORS

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 643-647
Author(s):  
A. K. Verma ◽  
R. Nandan ◽  
A. Verma
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Crop Growth ◽  
Microwave Spectrum ◽  
Rice Crop ◽  
Synthetic Aperture ◽  
Earth Surface ◽  
Knowledge Based ◽  
The Earth ◽  
Multi Temporal

<p><strong>Abstract.</strong> Space-based observation of crops and agro-system on the Earth surface is one of the most important applications of remote sensing using the sensors in optical and microwave spectrum to assess the crop growth for decision making for developing crop information and management system. Remote sensing technology provides scalable and reliable information in respect of rice crop grown area, its crop growth and prediction of crop yield due to acquisition of satellite imagery during the revisit of the orbit by space-borne sensors in optical and microwave spectrum. Synthetic Aperture Radar has the advantages of all-weather, day and night imaging, canopy penetration, and high-resolution capabilities, which makes Space-borne SAR sensors as an effective system for monitoring crop growth, crop classification and mapping of crop area based on the crop canopy interaction of SAR signals due to backscattering coefficients of the earth surface. SAR data from ERS-1/2 SAR, ENVISAT ASAR, ALOS-1/2 PALSAR, Radarsat-1/2 SAR, TerraSAR, COSMO-SkyMed, and Sentinel-1 have been used by various researchers for identification and analysis of rice crop growth based on the backscattering values in different regions of Asia and European region, where backscattered image depends of various earth surface and SAR sensors parameters. In this paper, knowledge based classifier using SAR images of existing space-borne-SAR sensors have been developed based on modeling of SAR backscattering coefficients in C-band and X-band for monitoring the rice crop growth and its analysis using multi-temporal and multi-frequency- SAR sensors data.</p>

scholarly journals Methods for Complexing Images Formed by Multi-Band Synthetic Aperture Radars

2021 ◽  
Vol 24 (3) ◽  
pp. 6-21
Author(s):  
A. A. Potapov ◽  
V. A. Kuznetsov ◽  
E. A. Alikulov
Keyword(s):  
Remote Sensing ◽  
Systems Approach ◽  
Decomposition Analysis ◽  
Synthetic Aperture ◽  
Joint Processing ◽  
Fractal Approach ◽  
Radar Images ◽  
The Earth ◽  
Synthetic Aperture Radars ◽  
Multi Band

Introduction. Synthetic aperture radars (SAR) are important components of aviation-based systems for remote sensing of the Earth. The current level of such systems allows simultaneous radar surveys in several frequency ranges. Such surveys require complexing of the images formed in each of the frequency channels, which task is yet to be resolved.Aim. To review the formation principles and methods for joint processing of images using space and aviation-based multi-band synthetic aperture radar systems.Materials and methods. The methodology of systems analysis, involving the integral stages of decomposition, analysis and synthesis, was used. Decomposition of integrating multi-band radar images was performed considering the effect of various factors on the characteristics of radar images in different frequency ranges. Such factors include the principles of radar imaging, issues of radar images of multi-band synthetic aperture radars with real characteristics, and complexing levels.Results. According to the classical systems approach, the results of review and analysis are corresponded by appropriate conclusions on the shortcomings of each decomposition element and the synthesis of a proposal for achieving the goal. It was shown that joint processing of multi-band radar images can be carried out at the levels of signals, pixels, features and solutions, as well as their aggregates. Each approach is characterised by its shortcomings, which impede implementation of full integration of multi-band radar images without loss of information, which is due to the absence of information redundancy of radar images, compared to, e.g., optical images.Conclusion. Recommendations on the application of a particular method and the synthesis of a system for radar complexing images based on the texture-fractal approach were formulated. Directions for further work meeting all the requirements for completeness, reliability and information content of remote sensing of the Earth were outlined.

scholarly journals Modelling complex for surface radar images in the “distance-angle” coordinates

2019 ◽  
Vol 30 ◽  
pp. 15011 ◽  
Author(s):  
Yury Markov ◽  
Alexander Bokov ◽  
Vladimir Vazhenin
Keyword(s):  
Electromagnetic Waves ◽  
Single Channel ◽  
Antenna System ◽  
Synthetic Aperture ◽  
Front Side ◽  
Software Complex ◽  
Radar Images ◽  
Radar Systems ◽  
Different Types ◽  
Synthetic Aperture Radars

The mathematical modelling software complex of monostatic radar systems is discussed in the article. It is aimed to model of typical radar scenarios with various conditions of an electromagnetic waves reflection from terrain. The received signals are used to synthesize radar images (portraits) of surfaces. The structure of the modelling complex allows studying of single-channel and multi-channel synthetic aperture radars with pulse and continuous types of modulation of signals reflected from underlying surfaces of different types. The complex can be useful to simulate radar portraits of the surrounding radar scene’s objects in the native “distance-angle” coordinates, including the nadir direction of the antenna system. The portraits for cases of front-side looking by a wide- pattern antenna in two adjacent directions are modelled and evaluated in the article.

scholarly journals DEVELOPMENT OF GEOINFORMATION SYSTEM FOR IDENTIFICATION AND TIME MONITORING OF DAMAGED LANDS DUE TO ILLEGAL EXTRACTION OF AMBER

2020 ◽  
Vol 46 (3) ◽  
pp. 136-144
Author(s):  
Oleksandr Yanchuk ◽  
Tetiana Dets ◽  
Olha Dmytriv ◽  
Serhii Ostapchuk ◽  
Andrii Prokopchuk ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Processing ◽  
Automated Identification ◽  
Geoinformation System ◽  
The Earth ◽  
Different Types

On basis of the analysis of existing elaborations determining places of the illegal extraction of amber by data of remote sensing of the Earth were established basic deciphering signs of the phenomenon researched. Methods were developed to identify lands damaged as a result of the illegal extraction of amber taking into account the specifics of data processing obtained from different types of satellite surveying systems: WorldView-2/3, Pleiades-1, Spot-6/7, Planet Scope, Sentinel-2B. The structure is substantiated and modular geoinformation system was developed on basis of GIS QGIS with added modules from open libraries GDAL, GRASS. The developed methods and modules of geoinformation system were tested on researched testing grounds with automated identification and calculation of areas of damaged lands.

scholarly journals MULTIDIMENSIONAL STATISTICAL MODEL FOR DETECTING OIL POLLUTION SITES BASED ON SATELLITE IMAGERY

2021 ◽  
Vol 4 (1) ◽  
pp. 11-16
Author(s):  
Alovsat Shura Guliyev ◽  
Tatiana A. Khlebnikova
Keyword(s):  
Remote Sensing ◽  
Statistical Model ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
Oil Spills ◽  
Oil Pollution ◽  
Sliding Window ◽  
Synthetic Aperture ◽  
The Earth ◽  
Homogeneous Regions

The article considers an algorithm for determining the statistical model from several inhomogeneous images of the Earth's surface obtained by different sensors (optoelectronic scanning device, synthetic aperture radar (SAR)) over the sea areas. The object of the study are the methods of remote sensing of the Earth used for detection and mapping of oil spills. The aim of the research was to perform testing for a possible variation of the statistical model inside a non-uniform sliding window based on a semi-automatic approach. The proposed algorithm makes it possible to determine the spatial extent of oil production sites and oil pollution in offshore waters using multi-time RSA data and a multi-zone combined image with a spatial resolution of 10 m. First, homogeneous regions are analyzed in the image, and then the model of the analysis zone is expanded to the more general case of inhomogeneous regions that are observed in the analysis windows.

scholarly journals Generalized-Capon Method for Diff-Tomo SAR Analyses of Decorrelating Scatterers

2019 ◽  
Vol 11 (4) ◽  
pp. 412 ◽  
Author(s):  
Fabrizio Lombardini ◽  
Francesco Cai
Keyword(s):  
Remote Sensing ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Full Model ◽  
Temporal Decorrelation ◽  
Sar Imaging ◽  
Profile Height ◽  
Differential Sar Interferometry ◽  
Dynamical Information

In synthetic aperture radar (SAR) remote sensing, Differential Tomography (Diff-Tomo) is developing as a powerful crossing of the mature Differential SAR Interferometry and the emerged 3D SAR Tomography. Diff-Tomo produces advanced 4D (3D+Time) SAR imaging capabilities, extensively applied to urban deformation monitoring. More recently, it has been shown that, through Diff-Tomo, identifying temporal spectra of multiple height-distributed decorrelating scatterers, the important decorrelation-robust forest Tomography functionality is possible. To loosen application constraints of the related main experimented full model-based processing, and develop other functionalities, this work presents an adaptive, just semi-parametric, generalized-Capon Diff-Tomo method, first conceived at University of Pisa in 2013, for joint extraction of height and dynamical information of natural distributed (volumetric) scatterers, with its formalization and a series of insights. Particular reference is given to the important functionality of the separation of different decorrelation mechanisms in forest layers. Representative simulated and P-band forest data sample results are also shown. The new Diff-Tomo method is getting a flexible and rich decorrelation-robust Tomography functionality, and is able to profile height-varying temporal decorrelation, for significantly distributed scatterers.

scholarly journals Deformation Monitoring Using Sentinel-1 SAR Data

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 344 ◽  
Author(s):  
Núria Devanthéry ◽  
Michele Crosetto ◽  
Oriol Monserrat ◽  
María Cuevas-González ◽  
Bruno Crippa
Keyword(s):  
Earth Observation ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Persistent Scatterer Interferometry ◽  
Sar Images ◽  
Persistent Scatterer ◽  
Deformation Velocity ◽  
Different Types ◽  
Processing Steps ◽  
Deformation Measurements

Satellite earth observation enables the monitoring of different types of natural hazards, contributing to the mitigation of their fatal consequences. In this paper, satellite Synthetic Aperture Radar (SAR) images are used to derive terrain deformation measurements. The images acquired with the ESA satellites Sentinel-1 are used. In order to fully exploit these images, two different approaches to Persistent Scatterer Interferometry (PSI) are used, depending on the characteristics of the study area and the available images. The main processing steps of the two methods, i.e.; the simplified and the full PSI approach, are described and applied over an area of 7500 km2 located in Catalonia (Spain). The deformation velocity map and deformation time series are analysed in the last section of the paper.

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