Synthetic Aperture Radar

This paper describes the analysis of L-band radiometric measurement data gathered with the synthetic aperture radiometer HUT-2D during several ground-based and airborne measurement campaigns. The radiometric data are analyzed from the instrument's performance point of view, aiming to verify the theoretical performance of an instrument of this kind and to assess the performance of the HUT-2D radiometer system in particular. The data sets considered for the study consist of measurements of well-known natural targets, such as cosmic background radiation, and measurements of pure water scenes, the brightness temperature of which is possible to model based on in situ measurements. We define four figures of merit, which are applicable for synthetic aperture radiometers. These are radiometric resolution, image bias, pixel-to-pixel random error, and temporal stability. Then, we use the selected data sets to assess these in the case of HUT-2D. The experimental results are discussed and compared to the theoretical values, where applicable. Also, we discuss possibilities to improve the presented performance. The main results of this paper are the consolidated performance parameters of the HUT-2D instrument. We study and discuss the properties of the error components related to the technology in a general level, and study the scalability of the errors as a function of the measured targets. In particular, the stability of the direction-dependent error component is pointed out, and a mitigation guideline is proposed.

An adaptive and fast constant false alarm rate (CFAR) algorithm based on automatic censoring (AC) is proposed for target detection in high-resolution synthetic aperture radar (SAR) images. First, an adaptive global threshold is selected to obtain an index matrix which labels whether each pixel of the image is a potential target pixel or not. Second, by using the index matrix, the clutter environment can be determined adaptively to prescreen the clutter pixels in the sliding window used for detecting. The G 0 distribution, which can model multilook SAR images within an extensive range of degree of homogeneity, is adopted as the statistical model of clutter in this paper. With the introduction of AC, the proposed algorithm gains good CFAR detection performance for homogeneous regions, clutter edge, and multitarget situations. Meanwhile, the corresponding fast algorithm greatly reduces the computational load. Finally, target clustering is implemented to obtain more accurate target regions. According to the theoretical performance analysis and the experiment results of typical real SAR images, the proposed algorithm is shown to be of good performance and strong practicability.

Polarimetric SAR interferometry (Pol-InSAR) is a radar remote sensing technique, that allows to extract forest heights by means of model-based inversion. Recently, there have been plenty of research on the retrieval of vegetation parameters by single frequency single baseline PolInSAR such as the ESPRIT method, three-stage inversion. However, these methods tend to underestimate the forest height due to attenutation of the electromagnetic waves in the ground medium. This paper proposes a method to improve the accuracy of forest height estimation. This method is based on a fusion of hybrid method extracting forest parameters and the coherence amplitude method. Finally, the simulated PolInSAR data are used to validate the proposed method.

The necessity to control all the activities within the marine environment is nowadays vital for most official authorities. Besides protecting the ecosystem and providing safety and surveillance along the transportation corridors, illegal immigration and sustainable economic activities are also issues to cover. Since early nineties, a lot of efforts have been devoted to develop monitoring systems based on transponders (VMS or AIS). Such systems use active on-board devices to track ship positions via satellite communications. Despite of their great performance, the experience has shown, however, that this approach does not have the required independency and other alternatives are necessary. Among them, the one gathering more benefits is the integration of remote sensing, specially Synthetic Aperture Radar (SAR), with operational transponders. Certainly, this solution provides redundancy, 7/24 and all-weather monitoring capability, independently from the targets to track.

Use of InSAR techniques in the study of unstable slopes has been suggested in recent works. However, in the ease of mass movements, which typically occur in high-relief terrain and are of limited areal extent, the detection of ground surface deformation is difficult. Moreover, the presence of vegetation cover and atmospheric effects introduces coherence loss and resolution problems in the analysis of interferometric pairs. Thus, extreme care must be taken in every step of interferometric SAR processing in order to obtain results that can be easily interpreted and be of practical utility in landslide hazard studies. The authors present the results of the application of InSAR and DInSAR techniques to a landslide test area located in the Southern Apennines. A number of SAR images was selected, whose dates coincide with periods of mass movement activity documented by in situ controls. DInSAR processing was conducted in order to assess the potential of satellite radar data for landslide monitoring. Coarse resolution is an important limiting factor for effective information extraction. Advanced processing approaches may help to overcome this limit

A system that conforms to FIPA specifications (standards) is a FIPAcompliant system, and can interoperate with any other heterogeneous systems which are FIPA-compliant also. The conversion of a Multi-Agent System (MAS) into a FIPA-compliant system (i.e. one that adheres to FIPA standards), is important to support interoperability across different MAS. A different approach to conforming a MAS to a FIPA-compliant one, other that the common one of converting the whole system to adhere to FIPA specifications, is the use of the FIPA-compliant gateways . In this paper we extent our work on the FIPA-compliant gateways and we demonstrate the successful interoperability of the gateways based on a MAS utilising an active digital library composed of multi-spectral images of the Earth, as part of the Synthetic Aperture Radar Atlas (SARA).

An integrated remote sensing/field ecology project was carried out to link the use of synthetic aperture radar (SAR) and other remotely sensed data to studies of landscape spatial heterogeneity and bird community ecology as a first step toward applications in predicting biodiversity. P-, L-, and C-band SAR data were collected over a section of the South Alligator River in Kakadu

A new graphical technique is developed that takes advantage of time-subsidence data collected from either traditional extensometer installations or from newer technologies such as fixed-station global positioning systems or interferometric synthetic aperture radar imagery, to accurately estimate storage properties of the aquifer and vertical hydraulic conductivity of semi-confining units. Semi-log plots of time-compaction data are highly diagnostic with the straight-line portion of the plot reflecting the specific storage of the semi-confining unit. Calculation of compaction during one-log cycle of time from these plots can be used in a simple analytical expression based on the Cooper-Jacob technique to accurately calculate specific storage of the semi-confining units. In addition, these semi-log plots can be used to identify when the pressure transient has migrated through the confining layer into the unpumped aquifer, precluding the need for additional piezometers within the unpumped aquifer or within the semi-confining units as is necessary in the Neuman and Witherspoon method. Numerical simulations are used to evaluate the accuracy of the new technique. The technique was applied to time-drawdown and time-compaction data collected near Franklin Virginia, within the Potomac aquifers of the Coastal Plain, and shows that the method can be easily applied to estimate the inelastic skeletal specific storage of this aquifer system.

Synthetic Aperture Radar (SAR) images are strongly corrupted by the speckle noise due to random electromagnetic waves interference. The speckle noise reduces the quality of images and makes their interpretation and analysis really difficult, so it's necessary to filter images to remove the noise in order to preserve as much as possible the most important features of the signals. To achieve this goal, in this paper we present an efficient method that reduces the speckle noise in SAR images, based on the Contourlet Transform (CT). The CT is a new image decomposition scheme that provides sparse representation of the data, constructed by combining two successive stages, applying in first a Laplacian pyramidal decomposition followed by a directional filter bank. This non-linear approach is designed to give a good representation of the geometrical content of the natural images. Recently, the Stationary version of the Contourlet Transform (SCT) has been proposed to preserve the shift-invariant property. In the present paper, we explore two different de-noising methods: the Bayesian Shrinkage based on a weighting factor that reduces noise by using the contourlet coefficients, and the Soft Thresholding based on the choice of the threshold that ensures adaptation to the noiseless signals. Hence, we present a comparative study of the results obtained through the SCT considering different stages of decomposition's levels and different kind of filters, and the Lee Adaptive Filter. A performance evaluation is realized to validate our methods.

The application of Synthetic Aperture Radar (SAR) techniques to classical radar altimetry offers the potential for greatly improved Earth surface mapping. This paper provides an overview of the progress of SAMOSA, Development of SAR Altimetry Studies and Applications over Ocean, Coastal zones and Inland waters, an on-going ESA-funded project. The main objective of SAMOSA is to better quantify the improvement of SAR altimetry over conventional altimetry on water surfaces. More specifically, it focuses on the reduction of SAR mode data to pulselimited altimeter data, and a theoretical modelling to characterize the expected gain between high Pulse Repetition Frequency (PRF) reduced SAR mode data and low PRF classical Low-Resolution Mode (LRM) data. To this end, theoretical modelling using the Crámer-Rao bound (CRB) will be used and the results will be compared to previous theoretical estimates [7], using an analysis akin to that in .

This paper describes a phased incremental integration approach for application of image analysis and data fusion technologies to provide automated intelligent target tracking and identification for airborne surveillance on board an Aurora Maritime Patrol Aircraft. The sensor suite of the Aurora consists of a radar, an identification friend or foe (IFF) system, an electronic support measures (ESM) system, a spotlight

Hydrology is the single most important abiotic factor in the formation and functioning of a wetland. Many limitations still exist to accurately characterizing wetland hydrology over large spatial extents, especially in forested wetlands. Imaging radar has emerged as a viable tool for wetland flood mapping, although the limitations of radar data remain uncertain. The influence of incidence angle on the ability to detect flooding in different forest types was examined using C-HH Radarsat-1 data (23.5°, 27.5°, 33.5°, 39.0°, 43.5°, and 47.0°) during the leaf-off and leaf-on seasons. The ability to detect flooding under leaf-on conditions varied much more according to incidence angle while forest type (open canopy tupelo-cypress, tupelo-cypress, and bottomland hardwood) had a greater effect during the leaf-off season. When all forest types were considered together, backscatter generally decreased with increasing incidence angle under all conditions (2.45 dB between 23.5°and 47.0°flooded, leaf-off; 2.28 dB between 23.5°and 47.0°not flooded, leaf-off; 0.62 between 23.5°and 43.5°flooded, leaf-on; 1.73 dB between 23.5°and 43.5°not flooded, leaf-on; slope was not constant between incidence angles), but the distinction between flooded and non-flooded areas did not decline sharply with incidence angle. Differentiation of flooded and non-flooded forests was similar during the leafoff and leaf-on seasons. The ability to detect inundation under forest canopies was less than expected at smaller incidence angles and greater than expected at larger incidence angles, based on the results of previous studies. Use of a wider range of incidence angles during the entire year increases the temporal resolution of imagery which may, in turn, enhance mapping of inundation beneath forest canopies.

The symmetric scattering characterization method (SSCM) has been recently introduced for high-resolution characterization of certain targets under coherent conditions. SSCM is based on the Poincaré sphere representation, which supports a high-resolution decomposition of symmetric target scattering, as well as assessment and validation of the backscatter coherence. In this paper, the SSCM is investigated for ship characterization using Convair-580 polarimetric synthetic aperture radar (SAR) data. It is shown that the target Poincaré parameters permit identification of dominant scatterers with a significant symmetric scattering component. The polarization orientation angle of these quasi-symmetric scatterers is used to derive an estimate of the ship's pitch angle, under certain conditions. The effect of SAR system focus setting errors and Doppler centroid mistracking on the SSCM performance is investigated. It is shown that the SSCM is sensitive to the system focus setting and Doppler centroid shift. The first-order effects of these errors can be removed prior to the application of the SSCM method.

Non-quadratic regularization based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point scatterers, or smooth regions. However, many scenes contain a number of such features. We develop an image formation technique that simultaneously enhances multiple types of features by posing the problem as one of sparse signal representation based on overcomplete dictionaries. Due to the complex-valued nature of the reflectivities in SAR, our new approach is designed to sparsely represent the magnitude of the complex-valued scattered field in terms of multiple features, which turns the image reconstruction problem into a joint optimization problem over the representation of the magnitude and the phase of the underlying field reflectivities. We formulate the mathematical framework needed for this method and propose an iterative solution for the corresponding joint optimization problem. We demonstrate the effectiveness of this approach on various SAR images.

Abstract: Sensor-management in tracking consists of sensor mode control and scheduling, target selection, and situation assessment. In a dynamic environment, airborne radar necessitates active mode control for the acquisition of a synthetic aperture radar (SAR) ...

Titan's vast equatorial fields of RADAR-dark longitudinal dunes seen in Cassini RADAR synthetic aperture images correlate with one of two dark surface units discriminated as ''brown'' and ''blue'' in Visible and Infrared Mapping Spectrometer (VIMS) color composites of short-wavelength infrared spectral cubes (RGB as 2.0, 1.6, 1.3 mm). In such composites bluer materials exhibit higher reflectance at 1.3 mm and lower at 1.6 and 2.0 mm. The dark brown unit is highly correlated with the RADAR-dark dunes. The dark brown unit shows less evidence of water ice suggesting that the saltating grains of the dunes are largely composed of hydrocarbons and/or nitriles. In general, the bright units also show less evidence of absorption due to water ice and are inferred to consist of deposits of bright fine precipitating tholin aerosol dust. Some set of chemical/mechanical processes may be converting the bright fine-grained aerosol deposits into the dark saltating hydrocarbon and/or nitrile grains. Alternatively the dark dune materials may be derived from a different type of air aerosol photochemical product than are the bright materials. In our model, both the bright aerosol and dark hydrocarbon dune deposits mantle the VIMS dark blue water ice-rich substrate. We postulate that the bright mantles are effectively invisible (transparent) in RADAR synthetic aperture radar (SAR) images leading to lack of correlation in the RADAR images with optically bright mantling units. RADAR images mostly show only dark dunes and the water ice substrate that varies in roughness, fracturing, and porosity. If the rate of deposition of bright aerosol is $0.1 mm/yr, the surface would be coated (to optical instruments) in a few years ARTICLE IN PRESS www.elsevier.com/locate/pss 0032-0633/$ -see front matter r

The various applications have been promised by the new generation of the spacecraft SAR data (i.e. Radarsat2 and TerraSAR-X), as the classification, the decomposition, and the modelling of the polarimetric synthetic aperture radar (SAR) data has been improved in recent years .This work is based on the fact that in order to extract the various patterns in distinctive field of studies, all the scattering matrix components are informative source of data. Different cross products of the complex scattering matrix channels (HH, HV, VH, and VV) that are involved in the phase and amplitude information are joined together to build instructive features. In the vector space, Fisher class separability algorithm will be tested, and the features with the best class separability, large distance between classes, and small within-class variances will be selected. As we measured the classification effectiveness of the individual features, we needed to choose a subset of the informative features from the nine originally available features. Finally, we combined all the educational information contents in order to classify desired images with the best overall accuracy.

The Polarimetric Synthetic Aperture Radar technique has provided various opportunities and challenges in agricultural activities mainly on crop management. The aim of this study is to investigate the sensitivity of 10 parameters derived from multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data, to crop height and canopy coverage (CC) of maize, sunflower, and wheat. The correlation coefficient values indicate a high correlation for maize during the early growing stage. The coefficient determinations (R2) of 0.82 and 0.81 indicate that there is a strong relationship between the maize height and SAR parameters including VV + VH and VV, respectively. The maize CC is well correlated with VV parameter (R2 = 0.73), but it is observed that at the later growing stage the correlation became weaker. This means that the sensitivity decreases with increasing vegetation cover growth. Compared to maize, the sensitivity of SAR parameters to wheat variables is often good at the early stage....

Satellite Radar Interferometry is a unique method that gives us a possibility to take measurements of a land subsidence on strictly determined huge areas and with precision state the time range. This method uses the phase signal difference between two SAR satellite images (Synthetic Aperture Radar). Until this time this method was successfully tested on underground coal mining areas in the Upper Silesian Coal Region, where it gave us information about land deformations, about its location, range and size. As a result of the research, an interferomtric image of LGOM area was processed. It presents two-month growth of land subsidence over the copper ore exploitation fields. In the following text the benefits from satellite radar interferometry in a field of mining areas protection are presented.

A new empirical model for the retrieval, at a field scale, of the bare soil moisture content and the surface roughness characteristics from radar measurements is proposed. The derivation of the algorithm is based on the results of three experimental radar campaigns conducted under natural conditions over agricultural areas. Radar data were acquired by means of several C-band space borne

The TerraSAR-L system is currently being designed in a Phase B definition study. The platform is optimized for and built around the 11 m x 2.9 m active phased array antenna of the L-band Synthetic Aperture Radar (L-SAR). The L-SAR features, on top of standard Stripmap and ScanSAR operations, full polarimetric capabilities, repeat-pass ScanSAR interferometry and a Wave Mode. Besides a major contribution to applications in areas of climate change and oceanography, the TerraSAR-L design responds specifically to requirements from interferometric applications. Being conceived as operational, the mission scenario is aiming at maximizing the exploitation of this SAR system. One key element of the TerraSAR-L operations strategy is a long-term systematic and repetitive acquisition scenario to ensure consistent data archives. The other important factor is a systematic processing of all acquired data to Single-look Slant-range Complex (SSC) products to facilitate higher-level product generatio...

The authors introduce maximum likelihood techniques for optimised discrimination between agricultural and wooded regions, based on a multitemporal sequencc of ERS images. The inherent resolution of the system is inadequate to make such a classification on an individual image. However, the different temporal change patterns of the two classes can be exploited. One approach uses joint annealed segmentation of the image sequence, providing optimised exploitation of the speckle model in determining the common set of region boundaries in the underlying radar cross-section. This is followed by maximum likelihood change detection using a normalised log temporal texture measure. This is shown to be superior to constructing the normalised log measure directly, including speckle fluctuations, followed by a single annealed segmentation process. Finally, it is demonstrated how simple filtering of this normalised log measure can provide reasonable classification with greatly reduced computation load. 0 IEE, 2001 /EE Proceedings online no. 20010114

The availability of long sequences of SAR data virtually at any location on the Earth allows an extensive evaluation of land cover dynamics, which is a well-known extension to image pair multitemporal analysis. In this work we show the first results of an extensive evaluation of one among these "hypertemporal" SAR sequences, with a stress on urban area monitoring.

In agriculture, there is growing interest in determining field spatial variability for implementing differential management practices, which should generate economic and environmental benefits. To date, the majority of studies involving remote sensing and differential management have focused on optical sensor systems. Less attention has been paid to synthetic aperture radar (SAR), despite the advantages of "all-weather" acquisition enabling information to

Experiments of the two-pass interferometric Synthetic Aperture Radar (IfSAR) technique shows that the method often gives poor result due to poor coherence and to different physical conditions. For this reason, the stereoscopic Synthetic Aperture Radar (SAR) method presents an important alternative for terrain mapping. To automate the image matching procedures and to reduce the requirement of GCPs is a major consideration in the generation of Digital Elevation Models (DEMs) from space-borne SAR data. This paper describes a pyramidal image matching scheme with an optimized parameter selection strategy and a region-growing technique to achieve a high level of automation for producing Digital Parallax Models (DPMs) from same-side image pairs. A DPM provides successful matched points of an image pair. The strategy is mainly based on the analysis of the maximal parallax in an image pair and a pyramidal geometry. A rigorous algorithm for space intersection is used to generate DEMs from DPM...

algorithms are widely used in inverse synthetic aperture radar (ISAR) imaging. In the standard RD algorithm, envelope alignment and autofocus are first applied to transform the original data into equivalent turntable target data, and then FFT is used for the image formation. Usually, the migration through resolution cells (MTRCs) due to target rotation is ignored. With the improvement of resolution or the increase of target size, MTRCs cannot be ignored and must be mitigated. For high speed moving targets, the most widely used 'stop-and-go' data model is violated. In this case, the mitigation of MTRCs becomes even more complicated. In the paper, technical issues associated with high resolution ISAR imaging of high speed moving targets are addressed. A preprocessing algorithm is first proposed to convert the non-coherent raw ISAR data into coherent data, then a keystone formatting algorithm developed for the imaging of slow ground moving targets in SAR is applied to mitigate the MTRCs owing to rotational motion, and, finally, a high resolution time -frequency analysis based range -instantaneous Doppler (RID) algorithm is used to produce the focused ISAR image. Numerical examples are provided to illustrate the performance of the proposed approach.

Synthetic Aperture Radar Interferometry (InSAR) is an alternative technique to obtain measurements of surface displacement providing better spatial resolution and comparable accuracy at an extremely lower cost per area than conventional surveying methods. InSAR is becoming more and more popular in monitoring urban deformations, however, the technique requires advanced tools and high level competence to be successfully applied. In this paper we report important results obtained by analyzing new high resolution SAR data in urban areas. Using the SARPROZ InSAR tool and integrating the results with Google Earth, we discovered the (not public) precise tracks of new subways lines in Shanghai by detecting the millimetric surface subsidence caused by tunnel excavation. T he data used in this work have been acquired by the Italian sensor Cosmo-SkyMed. About 1.2 million of individual and independent targets have been detected in 600 sqkm, revealing impressive details of the ground surface deformation. Through the high spatial resolution (about 2m) and millimetric sensitivity in the Line Of Sight (LOS), Cosmo is able to highlight very localized subsidence with remarkable accuracy.

In this paper, the potential use tf spaceborne polarimettic synthetic aperture radar (SAB) data in mapping landcover tripes and monitoring d@restation in tropics is studied, ttere, the emphasis is placed on several clearing practices a~d forest regeneration that can be characteri:.ed by usi~,g the sensitivity of SAB channels to vegetation biomass and canopy str~lcture. A supervised Bayes-Jan classifier designed fi)r SAIl signal statistics is employed to separate five classes: primar*j fi)rest, second-ar~j fi)rest, pasture-crops, quebradao, and disturbed forest. The Land C-band polarimetric SAIl data acquired during the shuttle imaging radar-C (SIII-C)/X-SAB space-shuttle ntission in 1994 are used as input data to the class{tier, The results are verified by field observation and comparison with the LancLsat data acquired in August (f 1994. The SAB data can delineate these five classes with approxinmtely 72% accuracy. The confusion arises wher~ separating old secondary fi)rests from primary .tim'st aad the young ones from pasture-crops. It is shown that Landsat and SAg data camj contplenwntary information about the vegetation structure that, when used i1~ sy~u¢r~,ism, may increase the classification accuracq over secondar~j fi~rest regrowth. When the number (f land-co~)er types was reduced to three classes including primanj fi~rest, pasture-crops, and regrowth-disturbed fi~rest, the acc~tracy of classification increased to 87%. A dinwnsionality anahjsis of the classifier showed that the accurac~j can be fi~rther improved to 92% by reducing the feature space to L-band HH and HV chantwls. Comparison of SIIl-C data acquired in April (wet period) a~ld October (dr~j period) indicates that multi

Although it is a time-domain method, the finitedifference time-domain (FDTD) method has been used extensively for calculating frequency domain parameters such as specific absorption rate, radar cross-section, and S-parameters. When a broad frequency band is of interest, using a broad-band pulsed excitation can provide this frequency response with a single FDTD simulation. The frequency domain data can be calculated from the time domain data using either a discrete Fourier transform (DFT) or a fast Fourier transform (FFT). This letter examines both methods and analyzes why the DFT is generally more efficient and easier to use than the FFT for FDTD time-tofrequency domain conversions.

Synthetic Aperture Radar (SAR) is an active microwave imaging method. It operates independently of Sun illumination and cloud coverage. Current spaceborne systems use wavelengths of 3 to 25 cm and achieve resolutions of 10 to 50 m. The paper attempts to explain the basic SAR imaging principles using a minimum of mathematics. Emphasis is put on the particular properties of SAR images that should be understood before interpreting these data.

Trihedral corner reflectors are the preferred canonical target for SAR performance evaluation for many radar development programs. The conventional trihedrals have problems with substantially reduced Radar Cross Section (RCS) at low grazing angles, unless they are tilted forward, but in which case other problems arise. Consequently there is a need for better low grazing angle performance for trihedrals. This is facilitated by extending the bottom plate. A relevant analysis of RCS for an infinite ground plate is presented. Practical aspects are also discussed.

Over the past decades, a number of different Synthetic Aperture Radar (SAR) techniques were developed for mapping the surface of the planets either from Earth or from orbiting spacecrafts. However, the idea to use radar to study the subsurface started to develop during the last 15 years. The ability of the radio waves to penetrate the ice, permafrost and arid surface was at the origins of the development of the Ground Penetrating Radars (GPR). GPRs have been widely applied on Earth with a large number of the scientific and industrial applications. The application of GPR to the space exploration relies on the same operation principle but requires the development of low power and low mass equipment. In this paper, we start by a short summary of the general electromagnetic behavior of the materials that determines the principal characteristics of ground penetrating instruments. Then we describe the GPR instrument that was developed for the Mars 1998 mission (unfortunately cancelled). Then, we discuss a general GPR design that can be implemented on future rover missions. The measurements from the surface cannot replace the global mapping from orbit using orbital radar sounders. MARSIS (Mars Advanced Radar for Subsurface and Ionospheric Sounding) [1]and SHARAD (SHAllow subsurface RADar) [2] radars are examples of these orbital radar sounders that are now in Mars orbit on the Mars Express (ESA) spacecraft and MRO (NASA). The Lunar radar Sounder (LRS) on the Japanese Kaguya (Selene) mission (2008 -2010) was the radar sounder on the Moon [9]

| We analyze the application of Shannon entropy and Bhattacharyya distance for the characterization of polarimetric interferometric synthetic aperture radar (PolInSAR) images. We discuss the relevance of the decomposition of the Shannon entropy of a homogeneous region into the sum of three physically meaningful terms that depend respectively on intensity, polarimetry, and interferometry. We also discuss an analogous decomposition property for the Bhattacharyya distance, which is an efficient measure of the contrast between two regions. We illustrate the application of this approach for analyzing different contributions in the information content of PolInSAR images.

Abstrac/-SAR surveys from separate passes show relative shifts of the ground wavcnu m ber spectra thaI depend on the local slope and the off-nadir angle. We discuss the exploitation of this spectral sllift for different app] ications: I) generation of "low noise" intcrferograms benefiting phase unwrapping, 2) generation of quick-look interferograms, 3) decorrelation redllction by means of tunable SAl{ systems (TINSAR), 1 4) range resolution enhancement, and 5) the combination of SAR data gathered by different platforms (airborne and satell ite) for a "long-lime coherence" sludy.

This paper presents a preliminary study about the scattering properties of urban-like scatters based on simulated SAR images. A simple target performed by a box of gypsum located over a perfectly conducting flat plane is analyzed for different views in both ISAR and SAR fully-polarimetric modes. The results are analyzed with the Pauli decomposition theorem and they show that the scattering response of such a target is dominated by a strong scatter, which polarimetric behavior depends on the relative orientation of the target with respect to the radar. Tests with interferometry shows that the height of the box can be reasonably retrieved despite of model simplicity.

Abstract—The launch of high-resolution remote sensing satel-lites like TerraSAR-X, WorldView, and Ikonos has benefited the combined application of synthetic aperture radar (SAR) and optical imageries tremendously. Specifically, in case of natural calamities or ...