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This study presents a remote sensing application of using time series Landsat satellite images for monitoring the solid waste disposal site (WDS). We propose a method of detecting high-rise buildings landfills, such as municipal dumps and solid waste, according to a radar image (the height of the ground level). For disposal site detection a variety steps of image processing used (calculation image average level of the earth's surface; filtering thresholds spectral brightness coefficients, the size of the connected components, the nature of reducing the level of height with the distance of the maximum level). The spatial geometric features of waste disposal facilities are analytically expressed by linear and radial characteristics from other objects of the earth surface. As a result, the proposed method demonstrates good accuracy in detection the solid waste disposal site on real satellite images.

The paper presents a synthetic information on a UAV-based radar terrain imaging system, its purpose, structure and working principle as well as terrain images obtained from flight experiments. A SAR technology demonstrator has been built as a result of a research project conducted by the Military University of Technology and WB Electronics S.A. under the name WATSAR. The developed system allows to obtain high resolution radar images, both in on-line and off-line modes, independently of the light conditions over the observed area. The software developed for the system allows to determine geographic coordinates of the imaged objects with high accuracy. Four LFM-CW radar sensors were built during the project: two for S band and two for Ku band, working with different signal bandwidths. Acquired signals were processed with the TDC algorithm, which allowed for a number of analyses in order to evaluate the performance of the system. The impact of the navigational corrections on a SAR image quality was assessed as well. The research methodology of the in-flight experiments of the system is presented in the paper. The projects results show that the developed system may be implemented as an aid to tactical C4ISR systems.

International audience; This paper investigates performance characteristics of similarity measures (SM) used in image registration domain to discriminate between aligned and not-aligned reference and template image (RI and TI) fragments. The study emphasizes registration of multimodal remote sensing images including optical-to-radar, optical-to-DEM, and radar-to- DEM scenarios. We compare well-known area-based SMs such as Mutual Information, Normalized Correlation Coefficient, Phase Correlation, and feature-based SM using SIFT and SIFT-OCT descriptors. In addition, a new SM called logLR based on log-likelihood ratio test and parametric modeling of a pair of RI and TI fragments by the Fractional Brownian Motion model is proposed. While this new measure is restricted to linear intensity change between RI and TI (assumption somewhat restrictive for multimodal registration), it takes explicitly into account noise properties of RI and TI and multivariate mutual distribution of RI and TI pixels. Unlike other SMs, distribution of logLR measure for the null hypothesis does not depend on registration scenario or fragments size and follows closely chi-squared distribution according to Wilks's theorem. We demonstrate that a SM utility for image registration purpose can be naturally represented in (True Positive Rate, Positive Likelihood Rate) coordinates. Experiments on real images show that overall the logLR SM outperforms the other SMs in terms of area under the ROC curve, denoted AUC. It also provides the highest Positive Likelihood Rate for True Positive Rate values below 0.4-0.6. But for certain registration problem types, logLR can be second or third best after MI or SIFT SMs. © 2016 SPIE..

Ground Control Points (GCP), automatically extracted from Synthetic Aperture Radar (SAR) images through 3D stereo analysis, can be effectively exploited for an automatic orthorectification of optical imagery if they can be robustly located in the basic optical images. The present study outlines a SAR/Optical cross-matching procedure that allows a robust alignment of radar and optical images, and consequently to derive automatically the corresponding sub-pixel position of the GCPs in the optical image in input, expressed as fractional pixel/line image coordinates. The cross-matching in performed in two subsequent steps, in order to gradually gather a better precision. The first step is based on the Mutual Information (MI) maximization between optical and SAR chips while the last one uses the Normalized Cross-Correlation as similarity metric. This work outlines the designed algorithmic solution and discusses the results derived over the urban area of Pisa (Italy), where more than ten COSMO-SkyMed Enhanced Spotlight stereo images with different beams and passes are available. The experimental analysis involves different satellite images, in order to evaluate the performances of the algorithm w.r.t. the optical spatial resolution. An assessment of the performances of the algorithm has been carried out, and errors are computed by measuring the distance between the GCP pixel/line position in the optical image, automatically estimated by the tool, and the “true” position of the GCP, visually identified by an expert user in the optical images.

Due to the unique imaging approach for ground-based radar, identification and classification in observation area is very difficult. In order to improve the accuracy of the calculation and application combine with other data resource. it is necessary to implement data matching of radar images and 3D laser point cloud. First, the 3D cloud should to be transformed to orthographic maps, and then the horizontal rotation and orbit attitude angle parameters would be estimated for similarity transformation according to the characteristics such as common points and lines. Finally, the same reference point of the ground-based SAR data and cloud data is employed to accomplished in a two-dimensional coordinate system (called local common coordinate system).

Global warming has caused serious damage to our environment in recent years. Accelerated loss of ice from Greenland and Antarctica has been observed in recent decades. The melting of polar ice sheets and mountain glaciers has a considerable influence on sea level rise and altering ocean currents, potentially leading to the flooding of the coastal regions and putting millions of people around the world at risk. Synthetic aperture radar (SAR) systems are able to provide relevant information about subsurface structure of polar ice sheets. Manual layer identification is prohibitively tedious and expensive and is not practical for regular, longterm ice-sheet monitoring. Automatic layer finding in noisy radar images is quite challenging due to huge amount of noise, limited resolution and variations in ice layers and bedrock. Here we propose an approach which automatically detects ice surface and bedrock boundaries using distance regularized level set evolution. In this approach the complex topology of ice and bedrock boundary layers can be detected simultaneously by evolving an initial curve in radar imagery. Using a distance regularized term, the regularity of the level set function is intrinsically maintained that solves the reinitialization issues arising from conventional level set approaches. The results are evaluated on a large dataset of airborne radar imagery collected during IceBridge mission over Antarctica and Greenland and show promising results in respect to hand-labeled ground truth.

Every vessel moving in the sea, imprints a perturbation on the wave structure of the sea and forms a so-called wake. These wakes can be used in the detection of a target and can also help in identifying its characteristics. Several studies concentrated on detection of a target wake by making use of either radar or infrared sensors. We model the infrared and radar signature of the wake and sea surface background and investigate the synergy between the two bands. The primary goal of this work is to make a comparative study between the two bands in order to be able to discriminate which sensor gives a more reliable detection in which scenario.

Recently, remote sensing is considering one of the most important tools in studies of water scattering and water characterization. Traditional methods for monitoring pollutants depended on optical satellite rather than Radar data. Thus, many of Water Quality Parameters (WQP) from optical imagery are still limited. In this paper, a new approach based on the TerraSAR-X images has been presented which it is used to map the region of interest and to estimate physical and chemical WQPs. This approach based on a Small Perturbation Model (SPM) for the electromagnetic scattering is applied by using the Elfouhaily spectrum. A series of inversions have been included in this model started by finding the reflectivity from backscattering coefficients which are calculated from SAR images. Another inversion has been applied to find dielectric constant from the calculation models of the reflectivity (in HH and VV polarizations). Then, a Stogryn Debye formulation has been used to estimate temperature and salinity of water surface from SAR images. After many derivations we got a new model able to estimate temperature and salinity directly from backscattering coefficients obtained from radar images. Inorganic chemical parameters which are represented by Total Dissolved Salts (TDS) and the Electrical Conductivity (EC) are estimated directly from salinity. A tow dataset of instu data have been used to validate this work. The validation included a comparison between parameters measured in situ and those estimated from Terra SAR-X image.

Slicks on the sea surface are characterized by attenuation of short wind waves and appeаr in radar imagery at moderate incidence angles as areas of reduced intensity. In the proximity of oil platforms, ship routes, fish farms, etc. marine slicks are often identified as oil spills or biogenic films. However, probability of false alarm when detecting film slicks is very high because of the occurrence of structures in radar images looking similar but not related to surface films (“lookalikes”). One of the most frequent "look-alikes" is wind depression areas (WDAs) where the wind excitation of short surface waves is reduced compared to the ambient background. Results of field observations of films slicks and WDA are described and differences in character of wind wave attenuation in different parts of the wind wave spectrum are revealed. Model calculations of wave damping degree (contrast) in film slick and in WDA are carried out and are shown to be in general agreement with experiment. Capabilities of dual-polarization and multi-band microwave radar for discrimination between film slicks and “look-alikes” are analyzed based on experiment and model results.

In this paper we propose to simulate SAR radar images that can be acquired by aircraft or satellite. This corresponds to a real problematic, in fact, an airborne radar data acquisition campaign, was conducted in the south east of France. We want to estimate the geometric deformations that a digital terrain model can be subjected. By extrapolation, this construction should also allow to understand the image distortion if a plane is replaced by a satellite. This manipulation allow to judge the relevance of a space mission to quantify geological and geomorphological data. The radar wave is an electromagnetic wave, they have the advantage of overcoming atmospheric conditions since more wavelength is large is better crossing the cloud layer. Therefore imaging radar provides continuous monitoring.

Correlation characteristics are important for sea clutter restraint in radar image processing, which is universal in certain features for both radar and optical image. The spatial-temporal dispersion relation contained in sea clutter, which usually fits into the sum of wind friction linear item and gravity wave item, is proved effective for sea clutter restraint recently. A sea clutter restraint method for mobile searching mode observation point, which is prevalent in maritime air-borne platform, is developed from a former restraint method for shore-based stationary radar. A new extraction method for intrinsic dispersion linear item parameter of sea clutter aiming at range profile of searching mode radar system is proposed, which forms the core of the restraint method. The statistical model is founded on spatial-temporal dispersion relation and radar illumination geometry. Simulation results shows Doppler shift of measured wind linear item have a bias from the sum of sea wind and radar platform velocity. A systematic study suggests the bias could be attributed to interaction between wind friction and gravity wave item, and a rather good fitting result is obtained. CFAR detection processing for a set of experimental clutter data shows that this intrinsic dispersion extraction method formula is found to be effective in detection probability enhancement. The restraint method based on the proposed dispersion extraction method could be utilized in mobile maritime surveillance equipments.

The proposed spaceborne NASA-ISRO SAR (NISAR) mission would use the repeat-pass interferometric Synthetic Aperture Radar (InSAR) technique to measure the changing shape of Earth’s surface at the centimeter scale in support of investigations in solid Earth and cryospheric sciences. Repeat-pass InSAR relies on multiple SAR observations acquired from nearly identical positions of the spacecraft as seen from the ground. Consequently, there are tight constraints on the repeatability of the orbit, and given the narrow field of view of the radar antenna beam, on the repeatability of the beam pointing. The quality and accuracy of the InSAR data depend on highly precise control of both orbital position and observatory pointing throughout the science observation life of the mission. This paper describes preliminary NISAR requirements and rationale for orbit repeatability and attitude control in order to meet science requirements. A preliminary error budget allocation and an implementation approach to meet these allocations are also discussed.

Ka-band RADAR frequency range has not yet been used for Synthetic Aperture Radar (SAR) from space so far, although this technology may lead to important applications for the next generation of SAR space sensors. Therefore, feasibility studies regarding a Ka-band SAR instrument have been started [1][2], for the next generation of SAR space sensors. In spite of this, the lack of trusted references on backscatter at Ka-band revealed to be the main limitation for the investigation of the potentialities of this technology. In the framework of the ESA project “Ka-band SAR backscatter analysis in support of future applications”, this paper is aimed at the study of wave interaction at Ka-band for a wide range of targets in order to define a set of well calibrated and reliable Ka-band backscatter coefficients for different kinds of targets. We propose several examples of backscatter data resulting from a critical survey of available datasets at Ka-band, focusing on the most interesting cases and addressing both correspondences and differences. The reliability of the results will be assessed via a preliminary comparison with ElectroMagnetic (EM) theoretical models. Furthermore, in support of future technological applications, we have designed a prototypal software acting as a “library” of earth surface radar response. In our intention, the output of the study shall contribute to answer to the need of a trustworthy Ka-Band backscatter reference. It will be of great value for future technological applications, such as support to instrument analysis, design and requirements’ definition (e.g.: Signal to Noise Ratio, Noise Equivalent Sigma Zero).

At present time radar methods of the seas and oceans diagnostics are actively developing. Using of the radar stations based on satellites and planes allows to receive information on a sea surface and a atmosphere near-surface layer with coverage of big water surface areas independently of day time. The developed methods of satellite radio images processing can be applied to marine radar stations. In Institute of Applied Physics RAS works on sea surface diagnostics systems development on the basis of standard marine radar are actively conducted. Despite smaller coverage of the territory in comparison with satellite data, marine radar have possibility to record spatially temporary radar images and to receive information on a surrounding situation quickly. This work deals with results of the researches which were conducted within the international expedition in the Atlantic Ocean in the autumn of 2012 on a route Rotterdam (Netherlands) – Ushuaya (Argentina) – Antarctica — Ushuaya. During this expedition a complex measurements of a sea surface, a atmosphere near-surface layer parameters and subsurface currents in the wide range of hydroweather conditions, including the storm were carried out. The system developed in IAP RAS on the basis of a marine radar ICOM MR-1200RII and the ADC (Analog Digital Converter) block for data recording on the personal computer was used. Display of a non-uniform near-surface current on sea surface radar images in storm conditions is shown. By means of the high-speed anemometer and meteorological station the measurements of the atmosphere parameters were carried out. Comparison of the anemometer data with calculated from radar images is carried out. Dependence of radar cross section from wind speed in the wide range of wind speeds, including storm conditions is investigated. Possibility of marine radar using for surface waves intensity and ice situation estimates also as icebergs detection is shown.

Radar manifestations of ship wakes in zones of phytoplankton bloom are discussed. It is shown that these signatures can be regarded as indicators of biogenic activity. The main data are satellite radar images. Satellite visible (VIS) and infrared (IR) satellite data are also analyzed. The large amount of the available data allowed us to make some generalizations and obtain statistically reliable results concerning spatial and temporal variability of certain type of ship wake manifestations in synthetic aperture radar (SAR) images of the sea surface. Traditional classification of surface ship wakes manifestations in satellite SAR images specifies distinct features such as a dark trailing centreline region (turbulent wake), narrow V-wakes aligned at some angle to the ship’s path (the Kelvin wake), and, sometimes, internal wave wakes generated under conditions of shallow stratification. Their characteristic lengths are reported to be up to tens of kilometers and they can last from tens of minutes up to one hour. Instances of radar signatures of the ship wakes dissimilar to the previously described were detected in radar images obtained in the course of a satellite monitoring campaign of the central and south-eastern Baltic. These ship wakes can be seen in satellite radar images as long bright strips of enhanced backscatter with characteristic length of up to several hundred kilometres lasting more than 5 hours. A hypothesis is put forward of the coherence of this type of ship wakes detected in sea surface radar imagery and areas of intensive biogenic activity under conditions of low near-surface winds. Statistics on their seasonal, spatial and year-to-year distribution are drawn. These results are compared with temporal and spatial variations in chlorophyll a concentration and intensity of phytoplankton bloom in the area of interest. Chlorophyll a concentration maps derived from satellite data are used, as well as those based on in situ measurements. The relation between occurrences of this type of ship wake manifestations and areas of algae blooms is established.

Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.

It is estimated that more than 20,000 natural lakes are found across China. Most of these lakes are undergoing eutrophication or other severe environmental nuisances owing to natural and/or anthropogenic processes. In order to prevent or to minimize such damaging impacts, and to ascer tain a proper quality management of the lake water and the associated fish resources, it is required to have access to up -to-date, accurate, and relevant data and information on the aquatic ecosystem in a timely manner. The “Dragon 3” project, supported by the European Space Agency, is focusing on Xin’an river watershed and investigates the impact of water quality and land cover/use change on the spatio-temporal distribution of the fishing grounds in Qiandao Lake . In this paper, the land use changes derived from satellite images is presented. Initially, Landsat 5 TM and Landsat 8 LDCM have been analyzed for the last 20 years in the vicinity of the Xin’an river watershed. Following the radiometric calibration of the images, several pixel-base classification algorithms have been evaluated including Spectral Angle Mapper (SAM), Support Vector Machine (SVM) as well Neural Network (NN). As it was found using the multi-temporal satellite imagery, the SVM algorithm was able to give high kappa accuracy estimated at around 0.90. In addition EO-Hyperion images over the western part of the Xin’an River were evaluated using hyperspectral vegetation indices as well using linear spectral un-mixing techniques. In addition, ENVISAT radar images have been evaluated in terms of land use change. The final outcomes indicate a significant urban expansion in the surrounding area of the Xin’an River which impacts the water quality investigation. Finally, a Landsat image was processed in order to estimate the Trophic State Index (TSI) values over the water bodies and the highest values were observed over the Xin’an river watershed and more specifically for the urban sites. Keywords: land use change; classification; un-mixing; optical remote sensing; radar; Trophic State Index

According to SAR imaging mechanism of underwater bathymetry, a 3-D hydrodynamic model based on SELFE (Semi-implicit Eulerian-Lagrangian Finite Element) is applied to demonstrate the temporal variations of the channel bathymetry changes. A microwave radar imaging of oceanic surface’s program of M4S is used to simulate the variation of normalized radar cross section (NRCS) induced by the ocean surface current. The simulation is carried out to study the effect of water depth changes and current variations on SAR imaging of channel bathymetry. The depth of channel is defined between 5 m to 17 m with an interval of every two meters. Six time of tide are used in the current variation simulation. The NRCS variation demonstrated in the simulated images are compared with in situ data, historical bathymetric maps and calibrated SAR images. All the four kinds of images manifest similar changes of channels, which proves that there is agreement between the simulation model used in this paper and other data. Simulation results also show that bigger depth change induces bigger NRCS variation. In the time of maximum ebb tide, simulated relative NRCS is bigger than others.

The dynamic responses of the polar ice sheets in Greenland and Antarctica can have substantial impacts on sea level rise. Understanding the mass balance requires accurate assessments of the bedrock and surface layers, but identifying each layer in ground-penetrating radar imagery must typically be performed by time-consuming hand selection. We have developed an approach for semi-automatically estimating bedrock and surface layers from radar depth sounder imagery acquired from Antarctica. Our solution utilizes an active contours method (level sets"), which identifies surface and bedrock boundaries by evolving initial estimates of a layer's position and depth until a gradient-based cost function is minimized. We evaluated the semi-automatic proposed method on 20 images with respect to hand labeled ground-truth. Compared to an existing automatic technique, our approach reduced labeling error by factors of 5 and 3.5 for tracing bedrock and surface layers, respectively.

Floods are among the most frequent and costly natural disasters in terms of human and economic loss and are considered to be a weather-related natural disaster. This study strives to highlight the potential of active remote sensing imagery in flood inundation monitoring and mapping in a catchment area in Cyprus (Yialias river). GeoEye-1 and ASTER images were employed to create updated Land use /Land cover maps of the study area. Following, the application of fully polarimetric (ALOS PALSAR) and dual polarimetric (ERS - 2) Synthetic Aperture Radar (SAR) data for soil moisture and inundation mapping is presented. For this purpose 2 ALOS PALSAR images and 3 ERS-2 images were acquired. This study offers an integrated methodology by the use of multi-angle radar images to estimate roughness and soil moisture without the use of ancillary field data such as field measurements. The relationship between soil moisture and backscattering coefficient was thoroughly studied and linear regression models were developed to predict future flood inundation events. Multi-temporal FCC images, classification, image fusion, moisture indices, texture and PCA analysis were employed to assist soil moisture mapping. Certain land cover classes were characterized as flood prone areas according to statistics of their signal response. The results will be incorporated in an integrated flood risk assessment model of Yialias catchment area.

The proposed method aims to reduce the spurious echoes in weather radar images collected at Melbourne radar site, using parameters from 2D-WTMM method based on the continuous wavelet transform, and including the PNN probabilistic neural network for the classification of pixels into two types of echoes : precipitation or parasite. Indeed, we propose the introduction of parameters related to wavelet transform skeletons, these parameters are proportional to the image texture roughness, anisotropy and the distance of separation between non-zero radar echoes cells and give good separation between rain and non-rain echoes. Radar image is first segmented with Voronoi’s cells according to the spatial distribution of Holder exponents. By comparing with a direct method of classification which takes into account only one parameter at a time by using a threshold, it was found that the combination of these three parameters with PNN approach improves the final results in terms of preserving precipitation echoes and elimination of weather radar clutter. Initial results show approximately the removal of 98% of clutter and preservation of 97% of precipitation echoes.

In 2011 a 9.0 magnitude earthquake occurred off the pacific coast of Tohoku area of Japan. Accompanied with the subsequent tsunami, it caused serious damages on buildings, infrastructures and so on, in the coast area. We made observations of the damaged areas by the NICT airborne X-band synthetic aperture radar (SAR) system, “Pi-SAR2”, immediately after the earthquake. Pi-SAR2 can produce fully polarimetric radar images with high spatial resolution of 0.3 m. The image data were used to estimate the damages in detail and quantitatively. We have found that the high resolution radar image data are useful to estimate damaged buildings, flooded areas and amount of debris. Multitemporal observations are essential to reveal those changes.

This paper proposes a novel approach to building change detection in Very High Resolution (VHR) Synthetic Aperture Radar (SAR) images. The proposed approach is based on three concepts: i) the selection of the proper scale of representation; ii) the extraction of information on changes associated with increase and decrease of backscattering at the selected building scale (hot-spots); and iii) the exploitation of the expected backscattering proprieties of buildings to detect new and fully destroyed buildings. Experimental results obtained on a data set made up of two COSMO-SkyMed (CSK®) spotlight images acquired in 2009 over the city of L'Aquila (Italy) before and after the earthquake that hit the region, demonstrated that the proposed approach allows an accurate identification of destroyed buildings while presents a low rate of false alarms.

An FM-CW radar at 94 GHz has been equipped with antennas with high azimuthal gain and a broad beam in elevation and mounted on a rotating pedestal. The radar covers a range interval of 500 m. A change detection algorithm is used to discriminate invading persons from the background. Tracking of non-stationary target objects is maintained by Kalman filtering. The RCS of detected objects is determined using a pre-calibration against a precision corner reflector at a defined range. The measured RCS is compared with a threshold value to discriminate between dangerous and nondangerous persons. Additional information from a video camera is necessary for a first discrimination between target classes.

This paper is concerned with the identification of grassland management using both optical and radar data. In that context, grazing, mowing and a mix of these two managements are commonly used by the farmers on grassland fields. These practices and their intensity of use have different environmental impact. Thus, the objectives of this study are, firstly, to identify grassland management practices using a time series of optical and radar imagery at high spatial resolution and, secondly, to evaluate the contribution of radar data to improve identification of farming practices on grasslands. Because of cloud coverage and revisit frequency of satellite, the number of available optical data is limited during the vegetation period. Thus, radar data can be considered as an ideal complement. The present study is based on the use of SPOT, Landsat and RADARSAT-2 data, acquired in 2010 during the growing period. After a pre-processing step, several vegetation indices, biophysical variables, backscattering coefficients and polarimetric discriminators were computed on the data set. Then, with the help of some statistics, the most discriminating variables have been identified and used to classify grassland fields. In addition, to take into account the temporal variation of variables, dedicated indexes as first and second order derivatives were used. Classification process was based on training samples resulting from field campaigns and computed according six methods: Decision Trees, K-Nearest Neighbor, Neural Networks, Support Vector Machines, the Naive Bayes Classifier and Linear Discriminant Analysis. Results show that combined use of optical and radar remote sensing data is not more efficient for grassland management identification.

Large wildfires in forests of southern European countries such as Portugal, Spain, Greece, France and Italy are one key ecological disturbance of the Mediterranean environment. Optical data have been largely used for burned area mapping and literature provides an extensive reference for the typical spectral signal of burns and the methodologies applied to extract burn perimeters. However, optical remote sensing techniques have the major limitation of a reduced frequency of clear images due to cloud cover; moreover, for the specific application of burned area mapping, unburned targets such as shadows, can be spectrally confused and misclassified as burns. For this reason radar images could be integrated as an additional source of information. We developed an approach for mapping burned areas in Mediterranean regions based on Landsat TM/ETM+ data and vegetation indices that provided satisfactory results. However, we are currently working for further improving our approach by exploiting the synergy between optical and radar data. In this paper we present the first results of the analysis of the SAR backscatter over burned areas for future integration into the formal framework previously developed. Although results are preliminary, they encourage us to test the approach over different regions of the Mediterranean environment to evaluate its robustness.

Satellite high-resolution radar data from Envisat ASAR, RADARSAT-2 and TerraSAR-X sensors are used for the detection and investigation of fine structure of currents and submesoscale eddies. The fine structure of sea currents is manifested in radar images as quasiperiodic slick strips of a horizontal scale from tens of meters to several kilometers. The strips are typically elongated along the currents apparently indicating their jet character and intermittence. The focus is on filamentary slick bands involved into small scale vortical processes and allowing estimation of spatial characteristics of submesoscale eddies based on their SAR signatures. Submesoscale or eddies with diameters of less than Rossby radius of deformation could hardly be investigated by traditional oceanographic means due to spontaneity of their appearance, nonstationarity and short lifetimes. Sources of their generation are still not well known. A large archive of satellite data accumulated during 1999-2011 over different parts of the Black, Baltic and Caspian Seas has been analyzed in order to search, systemize and reveal mechanisms of formation and evolution of small scale eddy structures in these areas. Atmospheric and hydrological fronts and current instability have been found to play a significant role in submesoscale eddies generation. Subsatellite measurements using acoustic Doppler profiler (ADCP) have been performed aimed at verification and adjustment of the results obtained based on satellite radar data. The formation and drift of a near-shore submesoscale anticyclonic eddies of 5-7 km in diameter were observed.

This study strives to highlight the potential of flood inundation monitoring and mapping in a catchment area in Cyprus (Yialias river) with the use of radar satellite images. Due to the lack of satellite data acquired during dates flood inundation events took place, the research team selected specific images acquired during dates that severe precipitation events were recorded from the rain gauge station network of Cyprus Meteorological Service in the specific study area. The relationship between soil moisture and precipitation was thoroughly studied and linear regression models were developed to predict future flood inundation events. Specifically, the application of fully polarimetric (ALOS PALSAR) and data acquired over different dates for soil moisture mapping is presented. The PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor carried by the ALOS (Advanced Land Observing Satellite) have quadruple polarizations (HH, VV, HV, VH). The amount of returned radiation (as backscatter echoes) that dictates the brightness of the image depends on factors such as the roughness, size of the target relative to the signal's wavelength, volumetric and diffused scattering. The variation in soil moisture pattern during different precipitation events is presented through soil moisture maps obtained from ALOS PALSAR and data acquired during different dates with different precipitation rates. Soil moisture variation is clearly seen through soil moisture maps and the developed regression models are used to simulate future inundation events. The results indicated the considerable potential of radar satellite images in soil moisture and flood mapping in catchments areas of Mediterranean region. 2012 SPIE.

Recent theory of compressed sensing (CS) has been widely used in many application areas. In this paper, we mainly concentrate on the CS in radar and analyze the distinguishing ability of CS radar image based on information theory model. The information content contained in the CS radar echoes is analyzed by simplifying the information transmission channel as a parallel Gaussian channel, and the relationship among the signal-to-noise ratio (SNR) of the echo signal, the number of required samples, the length of the sparse targets and the distinguishing level of the radar image is gotten. Based on this result, we introduced the distinguishing ability of the CS radar image and some of its properties are also gotten. Real IECAS advanced scanning two-dimensional railway observation (ASTRO) data experiment demonstrates our conclusions.

A millimetre wave (75 - 110 GHz) polarimetric RADAR system is demonstrated for the detection of threat objects concealed under clothing upon the human body at stand-off ranges of up to 25 metres. The system implements Swept Frequency Continuous Wave RADAR with low cost components to deliver a compact, UWB, high resolution (~ 1 cm) RADAR system capable of detecting, resolving and discriminating a wide spectrum of threat items concealed on the human body. Threat detection is autonomously rendered by application of a neural network to the scattered time domain polarimetric radar return, the system may be taught to alarm or reject certain classes of objects; allowing for highly specific through to broad spectrum threat detection. The authors present data for some simple envisaged threat scenarios at stand off ranges out to 25 metres.

The paper presents the test results of a mobile system for the protection of large-area objects, which consists of a radar and thermal and visual cameras. Radar is used for early detection and localization of an intruder and the cameras with narrow field of view are used for identification and tracking of a moving object. The range evaluation of an integrated system are presented as well as the probability of human detection as a function of the distance from radar-camera unit.

This paper presents an exploratory attempt to use high-resolution radar measurements for face identification in forensic applications. An imaging radar system developed by JPL was used to measure a human face at 670 GHz. Frontal views of the face were measured both with and without a ski mask at a range of 25 m. The realized spatial resolution was roughly 1 cm in all three dimensions. The surfaces of the ski mask and the face were detected by using the two dominating reflections from amplitude data. Various methods for visualization of these surfaces are presented. The possibility to use radar data to determine certain face distance measures between well-defined face landmarks, typically used for anthropometric statistics, was explored. The measures used here were face length, frontal breadth and interpupillary distance. In many cases the radar system seems to provide sufficient information to exclude an innocent subject from suspicion. For an accurate identification it is believed that a system must provide significantly more information.

Radar altimeter can map the global geoid with high precision. This paper presents a new concept of mutibeam delay/Doppler radar altimeter which combines a liner array of nadir receivers and a nadir transmitter. The delay/Doppler technology is applied in the along track, and the array signal processing technology in the cross track. The key innovation in this concept is that fan-beams form in both along track and across track, and range correction is applied in across track as in along track, so that it could provide high precision with wide swath. But the 3D-matrix store and processing of the raw data from receivers are much more complicated than a conventional radar altimeter and a delay/Doppler radar altimeter. It could provide height profile with high precision for left scene and right scene, respectively, and leave small footprints at far range as at near range. It could also lead to uniform cross section in each resolution cell.

It is the difficulties to radar image interpretation, present remote sensing investigation and assessment of geohazard is mainly dependent on the high-resolution optical images, resulting in limited ability to extract surface information. The main advantage of radar is that it provides superior penetration capability under any type of weather condition, and can be used in the day or night time, rich image information and so on for the risk assessment of landslide, especially in geohazard emergency; optical image cannot match this advantage. The use of the "5.12" earthquake-induced landslide hazard for the research prototype, elaborate unique advantages and technical support role of remote sensing technology in landslide investigation and risk assessment, from the basic terrain data acquisition, disaster background analysis, interpretation of landslide hazard, monitoring, mapping, etc. Use of airborne and satellite radar remote sensing and Multi-source data to composite analysis of hazard information, indicates that the better interpretation effect by field investigation. The research results of this paper have great reference value to emergency disaster prevention and reduction of occurred frequent and dangerous geohazard.

An approach toward real-time for radar through-the-wall (TTW) sensing is presented. The aim is to detect and classify human motions behind walls. In the future a system could support an operator with information on the activity in a closed room, e.g., in a hostage situation. To meet this objective, radar TTW measurements have been performed on moving person(s) inside a closed room and an MTI-based signal processing algorithm, using coherent subtraction between different frequency sweeps, has been developed. The radar was equipped with ridge horn antennas which were directed toward an outer door. For each measurement the radar frequency was swept between 5 and 10 GHz 1893 times, with a sweep sampling rate of ~94 Hz. A crucial algorithm parameter is the time distance between two subtracting sweeps, or the sweep difference. Fast and slow motions are captured by using separate sweep differences. Applying the algorithm to the TTW data, we find that human motions behind a door can be detected with the background well suppressed. Even a person who is standing still without breathing is fairly easy to detect. The results are promising with low false alarm rates and fast signal processing rates, enabling real-time operation capability.

The first steps of laser radar are discussed with the examples from range finding and designation. The followed successes in field tests and further fast development provided their wide use. Coherent laser radar, developed almost simultaneously, tried the ideas from microwaves including chirp technology for pulse compression, and Doppler mode of operation. This latter found a unique implementation in a cruise missile. In many applications, environmental studies very strongly rely upon the lidars sensing the wind, temperature, constituents, optical parameters. Lidars are used in the atmosphere and in the sea water measurements. Imaging and mapping is an important role prescribed to ladars. One of the prospective trends in laser radar development is incorporation of range and velocity data into the image information. Deep space program, even having not come to the finish, gave a lot for 3D imaging. Gated imaging, as one of the 3D techniques, demonstrated its prospects (seeing through scattering layers) for military and security usage. Synthetic aperture laser radar, which had a long incubation period, started to show first results, at least in modeling. Coherent laser radar baptized as the optical coherence tomography, along with the position sensitive laser radar, synthetic aperture laser radar, multispectral laser radar demonstrated very pragmatic results in the micro-scale applications.

Ship detection and tracking is significant to the safe navigation, harbor surveillance and naval defence. In practice, the ship cannot be properly detected and tracked due to the influence of the ambient or its moving attitude on its echo in some images of the sequence. To solve this problem, we proposed a method for ship detection and tracking with time sequential shipborne radar imagery. The method consists of the Kalman filter and the correlation matching technique. The Kalman filter is used to predict the search areas of the ship in the next frame. The correlation matching technique is applied to extract the position of the ship, which can automatically adjust the parameters of the Kalman filter. If the tracked ship is incapable of detection in current frame, to keep the ship tracking successively, the predicted position obtained by applying the Kalman filter can be used as the current position of the ship. It has been tested with 46 temporally consecutive X-band shipborne radar images to demonstrate the validity of the method. The result shows that the ship in the shipborne radar images can be properly de tected and tracked. Keywords: Ship tracking, ship detection, shipborne radar, Kalman Filter

Accurate co-registration of synthetic aperture radar (SAR) images is essential for SAR interferometric applications such as along track interferometry (ATI) and across track interferometry (XTI). In this paper, we present a non-linear and linear joint algorithm for the SAR image co-registration which could be used in highly rugged terrain. First, a slave image transformation is performed by a non-linear mapping which is based on free available SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Models) and orbit parameters of both tracks to correct the distortions related to different view angles. Second, we calculate linear offsets between master image and transformed slave image with ordinary correlation based method to correct the offsets related to orbital errors. Our initial results show the effectiveness of such algorithm in co-registering critical SAR images.

In synthetic aperture radar interferometry, permanent scatterers (PSs) can be regarded as a series of measurement points which is not or less influenced by temporal and geometrical decorrelation and atmospheric delay. How to effectively detect and identify PS from SAR images is one of the crucial procedures in PS interferometric system. In this paper, we present a complete procedure for the identification and exploitation of stable natural reflectors or permanent scatterers (PSs) starting from long temporal series of interferometric SAR images based on ICA. Using 4 SAR images at different time over Nanjing from satellites ENVISAT of European Space Agency, some experiments are then carried out to evaluate the performance of the proposed method both visually and quantitatively.

This work presents a method to suppress the sea clutter for radar images acquired from ordinary navigation radar sensors, which are incoherent radars working in X-band and horizontal polarization. The proposed method considers short temporal sequences of consecutive navigation radar images. This method, which is based on rotation-to-rotation correlation and the variation of sea clutter response with range, can be described as follows. 1) To cumulate the k (k>1) temporally consecutive images. 2) To fit the variation of the sea clutter intensity with range for every scan line of the cumulative image and to subtract the fitted sea clutter intensity from the cumulative image for every pixel. 3) To calculate the threshold value of detection by applying the Constant False Alarm (CFAR) model and the Probabilistic Neural Networks (PNN) model. 4) To threshold the resulting image with the obtained threshold. 5) To remove the false alarm by utilizing the flood fill algorithm to determine the connected area size of any probable target in the binary image. Temporal sequences of navigation radar images were used to test the performance of the proposed method. The results obtained show that the proposed method is able to reduce significantly the sea clutter from the radar images and detect efficiently a ship embedded in the sea clutter. The detection precision is provided according to the experimental results.

Radar altimeter can map the global geoid with high precision. This paper presents a new concept of mutibeam delay/Doppler radar altimeter which combines a liner array of nadir receivers and a nadir transmitter. The delay/Doppler technology is applied in the along track, and the array signal processing technology in the cross track. The key innovation in this concept is that fan-beams form in both along track and across track, and range correction is applied in across track as in along track, so that it could provide high precision with wide swath. But the 3D-matrix store and processing of the raw data from receivers are much more complicated than a conventional radar altimeter and a delay/Doppler radar altimeter. The scheme is of obvious advantages. It could provide height profile with high precision for left scene and right scene, respectively, and leave small footprints at as far range as at near range. It could also lead to uniform cross section in each resolution cell.

It is well known that synthetic aperture radars (SARs) can image oceanic internal waves (OIWs). The signatures of OIWs on SAR images result from the modulation of wind-generated surface waves by the surface currents associated with the OIWs. The role of surface winds in SAR signatures of OIWs in the northern South China Sea is examined using SAR images and BlendQscat wind data. A radar imaging model for simulating SAR signatures of OIWs is also used to estimate the dependence of the radar signatures associated with OIWs on wind conditions. The results show that the signatures of OIWs on SAR images in the northern South China Sea are highly dependent on the wind speed. The temporal variations of the OIWs observed by SAR are closely related with the temporal variations of the wind speed in the study area.

Some missions have been carried out to measure wave directional spectrum based on airborne real aperture radar in a low incidence. For this study, the authors simulate the satellite-based real aperture radar image spectrum to validate the radar performance of measuring the directional wave spectrum based on the same principal as airborne one. In the processes of the simulation, the authors don’t take into account the rotation of antenna and the disturbing of the noise in order that the simulation can exclude other factors to purely verify the measuring theory feasibility in essence. The authors use Wen’s spectrum as the input spectrum of the simulation, which is a kind of wind-generated wave spectrum that can better describe the state of developi ng wave and the statuses of the Chinese sea fields. Following that, the simulated sea surface, backscatte red radar signal, modulation spectrum and the one dimension wave spectrum (two dimension one can be obtained by synthesizing every directional one dimension spectrum) are obtained, which is compared with the input spectrum. To have a comprehensive realization to the performance of the radar, different cases including different developing degree, wind speed and angle between dominant waves propagation direction and radar look direction are considered. Presen ted results show that Satellite-based real aperture radar can mostly measure the wave spectrum, but the capacity is limited on the cases of low wind speed, developing waves and the big angles. Keywords: Satellite-based real aperture radar, Wen’s wave spectrum, wave directional spectrum

With the development of laser technology, Three-Dimensional (3D) imaging sensors based on Laser Radar (LADAR) gradually possess vast application in complicated battlefield of modern warfare. LADAR can detect much more targets than other sensors, such as infrared imaging and radar imaging. Range image and intensity image can be obtained through using LADAR, and they are suitable for automatic target recognition. At present the research of automatic target recognition technology for LADAR is a hot problem. Main work of this paper is composed of three parts: Firstly, current research and application of automatic target recognition technology for LADAR are demonstrated; Secondly, main problems in automatic target recognition for LADAR are thoroughly analyzed, including problems in five stages: preprocessing, target detection, feature extraction, founding pattern database and performance evaluation; Finally, a detailed survey is set forth about technical approach of automatic target recognition for LADAR, including six components: preprocessing, target detection, feature extraction, recognition, modeling and simulation, performance evaluation.

One of the main problems in ship detection is the presence of sea clutter inherent to radar imagery. A moving ship detection method with time sequential shipborne radar imagery has been developed based on the radar backscattering properties of ships. The method consists of the coherence image computation, ship detection threshold estimation and false alarm removal. It has been tested with the X-band shipborne radar imagery. The results show that the method works well.

Geographical information systems (GIS) have been the base for radar ground echo simulations for many years. Along with digital elevation model (DEM), present GIS contain characteristics of terrain. This paper proposes a computationally sensible simulation procedure to produce realistic radar terrain signatures in a form of raw data of airborne pulse Doppler radar. For backscattering simulation, the model of the ground is based on DEM and built with point-form backscattering objects. In addition to the usual DEM utilization for xyz coordinates and shadowed region calculation, we assume that each data point in GIS describes several scatterers in reality. Approaching the ground truth, we distribute individual scatterers with adjustable attributes to produce authentic response of areas such as sea, fields, forests, and built-up areas. This paper illustrates the approach through an airborne side-looking synthetic aperture radar (SAR) simulation. The results prove the enhanced fidelity with realistic SAR image features.

Sensor and ground measurements can be considered as different representation of soil moisture characteristics. Sensor measurements, i.e. radar acquisitions, are synoptic and can cover wide areas but are influenced by other parameters such as roughness and vegetation. On the other side ground measurements are more related to soil moisture but because of the large variability of soil moisture often require some interpolation techniques to be later compared to satellite data. This paper presents an approach denominated Group Inversion Approach which aims at detecting the stable soil moisture characteristics starting from all kind of measurements available. Being reliable these points can be subsequently used to infer information about the mean soil moisture content over an area, such as a whole watershed. The soil moisture estimated from different inversion approaches are compared among them and with the ground data in relation with field characteristics. In this preliminary analysis the field characteristics have been extracted by the SAR images considering their semi-variograms. The preliminary results indicate that those fields with lowest inversion errors individuate mean field soil moisture values in good agreement with mean watershed soil moisture values.

A common assumption concerning noise in radar images is that it is of multiplicative nature and spatially uncorrelated. Meanwhile, recent studies have shown that additive noise component cannot be neglected, especially for images formed by side look aperture radars (SLARs). Moreover, majority of radar image filtering techniques are designed under assumption that noise is i.i.d., i.e. spatially uncorrelated. However, in many practical situations the latter assumption is not true. Besides, spatial correlation properties of noise can be different and they are often a priori unknown. In this paper we demonstrate that complex statistical and spatial correlation characteristics of noise in radar images can and should be taken into consideration at image filtering stage. We design a modification of the denoising algorithm based on discrete cosine transform (DCT) that is able to easily incorporate a priori information or obtained estimates of noise statistical and spatial correlation characteristics. This can be done in automatic (blind) manner due to utilizing a sequence of blind estimation operations. We present simulation results that show appropriate accuracy and robustness of these operations. Finally, real life image filtering examples are given that confirm the effectiveness of the designed techniques.

This paper describes the research efforts made at the Swedish Defence Research Agency (FOI) concerning through-the-wall imaging radar, as well as fundamental characterization of various wall materials. These activities are a part of two FOI-projects concerning security sensors in the aspects of Military Operations in Urban Terrain (MOUT) and Homeland Defence. Through-the-wall high resolution imaging of a human between 28-40 GHz has been performed at FOI. The UWB radar that was used is normally a member of the instrumentation of the FOI outdoor RCS test range Lilla Gara. The armed test person was standing behind different kinds of walls. The radar images were generated by stepping the turntable in azimuth and elevation. The angular resolution in the near-field was improved by refocusing the parabolic antennas, which in combination with the large bandwidth (12 GHz) gave extremely high resolution radar images. A 3D visualization of the person even exposed the handgun tucked into one hip pocket. A qualitative comparison between the experimental results and simulation results (physical optics-based method) will also be presented. The second part of this paper describes results from activities at FOI concerning material characterization in the 2-110 GHz region. The transmission of building, packing and clothing materials has been experimentally determined. The wide-band measurements in free space were carried out with a scalar network analyzer. In this paper results from these characterizations will be presented. Furthermore, an experimental investigation will be reported of how the transmission properties for some moisted materials change as a function of water content and frequency. We will also show experimental results of how the transmission properties of a pine panel are affected when the surface is coated with a thin surface layer of water.

Radar simulation involves the computation of a radar response based on the terrains normalized radar crosssection (RCS). In the past dierent models have been proposed for modeling the normalized RCS. While beingaccurate in most cases they lack intuitive handling. We present a novel approach for computing the meannormalized radar cross section for use in millimeter wave radar simulations based on Phong lighting. This allowsus to model radar power return in an intuitive way using categories of diuse and specular re”ections. Themodel is computational more ecient than previous approaches while using only few parameters. Furthermore,we give example setups for dierent types of terrain. We show that our technique can accurately model dataoutput from other approaches as well as real world data.Keywords: imaging radar, radar simulation, Phong lighting, millimeter wave radar, normalized radar crosssection, BRDF 1. INTRODUCTION The task of radar simulation comprises at least two aspects. The “rst is to generate a radar image where eachpart of the scene geometry is mapped to the appropriate location on the radar screen. This involves carryingout non-linear transformations of the objects that are to be displayed. For a more comprehensive descriptionthe reader is refered to Peinecke et al.