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To achieve high-resolution two dimension images, synthetic aperture radar (SAR) with ultra wide-band faces considerably technical challenges such as long data collection time, huge amount of data storage and high hardware complexity. In these years, several imaging modalities based on compressive sensing (CS) have been proposed which can provide high-resolution images using significantly reduced number of samples. However, the CS-based methods are sensitive to noise and clutter. In this study, a new imaging modality based on Bayesian compressive sensing (BCS) is proposed along with a novel compressed sampling scheme. Clutter, which the previous CS-based methods not considered, is also included in this study. This new imaging scheme requires minor change to traditional system and allows both range and azimuth compressed sampling. Also, the Bayesian formalism accounts for additive noise encountered in the compressed measurement process. Experiments are carried out with noisy and cluttered imaging scenes to verify the new imaging scheme. The results indicate that the Bayesian formalism can provide a sharp and sparse image absence of side-lobes, which is the common problem in conventional imaging methods and has fewer artifacts compared with the previous version of CS-based methods. [ABSTRACT FROM AUTHOR]

This study investigates a method using multi-temporal, multi-polarization ENVISAT (Environmental Satellite) Advanced Synthetic Aperture Radar (ASAR) data for mapping an agricultural area in a sub-tropical cloud-prone and rainy area of Pearl River Delta in south China. A total of six scenes of HH (radio waves transmitted and received in horizontal polarization) and VV (radio waves transmitted and received in vertical polarization) polarization ASAR data acquired from March to November 2006 were used for land cover classification. Meanwhile, four field surveys of 320 test sites were carried out simultaneously with ASAR image acquisition in May, July, September and November 2006. A decision tree classifier is used to classify seven main types of land cover features including sugarcane, banana fields, lotus ponds, fish ponds, mangrove wetland, seawater and buildings. As a result, a classification map of Nansha Island was generated with overall accuracy of 80% and a kappa coefficient of 77%. The results show that the multi-temporal and multi-polarization ASAR images can have good performance in separating the basic land cover categories in a sub-tropical cloud-prone and rainy area. The decision tree classifier is also approved to work efficiently on satellite SAR images with good classification accuracy. The analysis to get the best combination of radar scenes for the decision tree also proves that multi-temporal radar backscatter information received in the crop growth period is important in improving classification accuracy. [ABSTRACT FROM AUTHOR]

In land-use/land-cover change (LULCC) mapping, training fields for changed classes are often difficult to identify. In this study, a new sampling strategy is proposed for mapping LULCCs, in which change and no-change samples are obtained directly from overlaid bi-temporal images with a small shift or rotation. In this way, the artificial changes created maintain a certain degree of geographic information. This method is compared with a simulated sampling approach in which training samples of each land-use/land-cover type are selected separately from individual images and then cross-combined to form the 'from-to' classes. The case study demonstrates that both sampling strategies ease the difficulties in performing one-pass classification for LULCC detection and yield more accurate LULCC maps than that of the traditional two-step post-classification comparison method. Between the two sampling strategies, the proposed one provides higher testing accuracy than the simulated sampling approach, while the latter is easier to implement. [ABSTRACT FROM AUTHOR]

The objective of this research is to evaluate Quickbird multi-spectral (MS) data, multi-temporal RADARSAT Fine-Beam C-HH synthetic aperture radar (SAR) data and fusion of Quickbird MS and RADARSAT SAR for urban land-use/land-cover mapping. One scene of Quickbird multi-spectral imagery was acquired on 18 July 2002 and five-date RADARSAT fine-beam SAR images were acquired during May to August 2002. Quickbird MS images and RADARSAT SAR data were classified using an object-based and rule-based approach. The results demonstrated that the object-based and knowledge-based approach was effective in extracting urban land-cover classes. For identifying 16 land-cover classes, object-based and rule-based classification of Quickbird MS data yielded an overall classification accuracy of 87.9% (kappa: 0.868). For identifying 11 land-cover classes, object-based and rule-based classification of RADARSAT SAR data yielded an overall accuracy: 86.6% (kappa: 0.852 ). Decision level fusion of Quickbird classification and RADARSAT SAR classification was able to take advantage of the best classifications of both optical and SAR data, thus significantly improving the classification accuracies of several land-cover classes (25% for pasture, 19% for soybeans, 17% for rapeseeds) even though the overall classification accuracy of 16 land-cover classes increased only slightly to 89.5% (kappa: 0.885). [ABSTRACT FROM AUTHOR]

This paper investigates the potential of accounting for temporal contextual information in order to improve the accuracy of land-cover classification in summer with Synthetic Aperture Radar (SAR) data. Bi-temporal multi-sensor datasets collected in the Nonsan area of Korea were used to illustrate this approach. Multi-sensor data, including Japanese Earth Resources Satellite (JERS)-1 Optical Sensor (OPS) data acquired in April, and three different SAR sensor datasets from European Resource Satellite (ERS)-2, JERS-1, and Radarsat-1 obtained in the following July, were used for supervised classification in July. By comparing the classification result in April with a training set in July, transition probabilities between land-cover classes in the April-July period were empirically estimated and regarded as the temporal contextual information. A tau model is applied as a main integration methodology to combine multiple SAR data and the temporal contextual information. From the evaluation of the classification results in terms of accuracy statistics, using multiple SAR sensor data showed an increase of about 29% in overall accuracy compared with the case of single SAR sensor data. The incorporation of temporal contextual information into scattering information greatly contributed to a significant improvement of about 25% in overall accuracy over multiple SAR sensor integration only, and showed the best discrimination capability. [ABSTRACT FROM AUTHOR]

Ground moving target indication (GMTI) is one of the most important applications of the bistatic synthetic aperture radar (SAR) system as well as the monostatic system. An algorithm for moving target detection and location is presented with an azimuth-invariant bistatic multichannel SAR, which consists of one transmitter (channel) and multireceivers (multichannel). The algorithm is based on the discussion of the particularities of the bistatic SAR configuration including coherence improvement and clutter characteristics. Then, the corresponding compensating methods including two-dimensional range-azimuth prefiltering and bistatic differential range correction are proposed to solve these particularities. It is shown that using the compensating methods, the stationary clutter can be suppressed and the moving parameters of ground targets can be estimated accurately. Finally, simulation results demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

A high-frequency asymptotic technique based on the Uniform Geometric Theory of Diffraction (UTD) is employed for building interior imaging. The analysis is implemented using a ray-tracing technique to account for multiple scattering interactions in a building, along with a set of heuristic diffraction coefficients for dielectric wedges and corners. Imaging of the synthetic aperture radar data is carried out by the conventional fast Fourier transform method to transform to the downrange domain, and combined with a coherent near-zone imaging function for cross-range. Comparisons with experimental data for a scaled-down building model are given to demonstrate the suitability and efficacy of our analysis for through-wall building imaging. The UTD ray mechanisms account for the dominant scattering features observed in the image. [ABSTRACT FROM AUTHOR]

An optimal antenna height and power determination is proposed for the cost-effective implementation of the spaceborne stripmap synthetic aperture radar (SAR) satellite. For a given azimuth resolution, the antenna height and the average transmitted RF power of the SAR antenna are determined so that the mass per swath width of a SAR satellite can be minimized with the constraints on the signal-to-noise ratio (SNR) and ambiguities, given the SAR geometry (an altitude and an incidence angle) and radar wavelength. The illustrative design example shows that the mass per swath width of a SAR satellite, obtained from the proposed optimization, for the required SNR (SNRreq = 10 dB) and the specified incidence angle (η = 45 deg), is about 72% of that resulted from utilizing the minimum antenna height. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of multitemporal/polarization C-band SAR data for land-cover classification. Multitemporal Radarsat-1 data with HH polarization and ENVISAT ASAR data with VV polarization acquired in the Yedang plain, Korea are used for the classification of typical five land-cover classes in an agricultural area. The presented methodologies consist of two analytical stages: one for feature extraction and the other for classification based on the combination of features. Both a traditional SAR signal property analysis-based approach and principal-component analysis (PCA) are applied in the feature extraction stage. Special concerns are in the interpretation of each principal component by using principal-component loading. The tau model applied as a decision-level fusion methodology can provide a formal framework in which the posteriori probabilities derived from different sensor data can be combined. From the case study results, the combination of PCA-based features showed improved classification accuracy for both Radarsat-1 and ENVISAT ASAR data, as compared with the traditional SAR signal property analysis-based approach. The integration of PCA-based features based on multiple polarization (i.e. HH from Radarsat-1, and both VV and VH from ENVISAT ASAR) and different incidence angles contributed to a significant improvement of discrimination capability for dry fields which could not be properly classified by using only Radarsat-1 or ENVISAT ASAR data, and thus showed the best classification accuracy. The results of this case study indicate that the use of multiple polarization SAR data with a proper feature extraction stage would improve classification accuracy in multitemporal SAR data classification, although further consideration should be given to the polarization and incidence angle dependency of complex land-cover classes through more experiments. [ABSTRACT FROM AUTHOR]

The estimation of geophysical parameters from Synthetic Aperture Radar (SAR) data necessitates well-calibrated sensors with good radiometric precision. In this paper, the radiometric calibration of the new Advanced Synthetic Aperture Radar (ASAR-ENVISAT) sensor was assessed by comparing ASAR data with ERS-2 and RADARSAT-1 SAR data. By analysing the difference between radar signals of forest stands, the results show differences of varying importance between the ASAR on the one hand, and the ERS-2 and the RADARSAT-1 on the other. For recent data acquired at the end of 2005, the difference varies from -0.72 to +0.72 dB, with temporal variations that can reach 1.1 dB. For older data acquired in 2003 and 2004, we observe a sharp decrease in the radar signal in the range direction, which can attain 3.5 dB. The use of revised calibration constants provided recently by the European Space Agency (ESA) significantly improves the results of the radiometric calibration, where the difference between the ASAR and the other SARs will be lower than 0.5 dB. [ABSTRACT FROM AUTHOR]

In this Letter, a method is proposed for interferometric synthetic aperture radar (SAR) phase unwrapping based on image segmentation. An auxiliary phase map was generated and the interferometric phase was divided into many connected regions without discontinuity by separation and combination operations. A local optimal strategy was used to combine these regions with as few discontinuities as possible. The coherence map is not necessary. The authors compared the proposed method with Goldstein's branch-cut algorithm (BC) and the weighted multi-grid algorithm (WMG), demonstrating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The problem of automatically extracting building dimensions from synthetic aperture radar (SAR) image sequences of urban scenes is considered. An algorithm based on the delineation of shadows using active contours constrained by a simple wire-frame building model has been developed and demonstrated using SAR imagery of a village on Salisbury plain. The core of the algorithm is a novel technique for target delineation involving multiple active contours evolving simultaneously. In particular, a technique referred to as multiple hypothesis delineation, in which contours can be in several states simultaneously, is developed and shown to lead to considerable improvement in convergence time and delineation accuracy when used to delineate multiple targets in close proximity. The technique is applied to the automatic estimation of building dimensions by delineation of shadows in a sequence of SAR images of an urban scene. The estimation of building dimensions is automatic; user interaction is limited identifying a building of interest and a region of background clutter close to the building. Results are presented for six different buildings, in each case two SAR images were used in the estimation process separated in illumination angle by either 28° or 90°. The estimates of building dimensions are compared with the actual building dimensions obtained from architectural drawings. The algorithm was found to perform robustly and provide reasonably accurate estimates of the building dimensions, typically within ∼10% of the true values. [ABSTRACT FROM AUTHOR]

This paper introduces the innovative concept of multidimensional waveform encoding for spaceborne synthetic aperture radar (SAR). The combination of this technique with digital beamforming on receive enables a new generation of SAR systems with improved performance and flexible imaging capabilities. Examples are high-resolution wide-swath radar imaging with compact antennas, enhanced sensitivity for applications like along-track interferometry and moving object indication, and the implementation of hybrid SAR imaging modes that are well suited to satisfy hitherto incompatible user requirements. Implementation-specific issues are discussed and performance examples demonstrate the potential of the new technique for different remote sensing applications. [ABSTRACT FROM AUTHOR]

This paper proposes a new autofocusing method for synthetic aperture radar (SAR) imaging of complex moving structures such as ships on the ocean. This method is well suited for linear uniform motion as well as for nonuniform motion that may be caused by ocean waves. The key step is a modified adaptive notch filter (ANF) that can retrieve phase modulation due to motion. Simulation examples and real SAR results are presented. [ABSTRACT FROM AUTHOR]

A synthetic aperture radar system can be made compatible with other interleaved modes if the impact of the interruptions in operation necessary to accommodate these can be ameliorated. The ways in which this might be done are discussed. Effects of regular and random interruptions are characterised by simulation and analysis. Two methods of image enhancement, based on interpolation and apodisation, are then discussed; the latter appears to hold more promise of practical usefulness. [ABSTRACT FROM AUTHOR]

Progress in the study of space-surface synthetic aperture radar is presented. Global navigation satellite system is considered as the transmitter of opportunity. It highlights the various important issues to successfully obtain an image. The experimental testing of the imaging algorithm is presented and verified using a GLONASS satellite signal. [ABSTRACT FROM AUTHOR]

In this paper, the novel inverse synthetic aperture secondary radar wireless positioning technique is introduced. The proposed concept allows for a precise spatial localization of a backscatter transponder even in dense multipath environments. A novel secondary radar signal evaluation concept compensates for the unknown modulation phase of the returned signal and thus leads to radar signals comparable to common primary radar. With use of this concept, inverse synthetic aperture radar algorithms can be applied to the signals of backscatter transponder systems. In simulations and first experiments, we used a broadband holographic reconstruction principle to realize the inverse synthetic aperture approach. The movement of the transponder along a short arbitrary aperture path is determined with assisting relative sensors (dead reckoning or inertia sensors). A set of signals measured along the aperture is adaptively focused to the transponder position. By this focusing technique, multipath reflections can be suppressed impressively and a precise indoor positioning becomes feasible. With our technique, completely new and powerful options for integrated navigation and sensor fusion in RF identification systems and wireless local positioning systems are now possible. [ABSTRACT FROM AUTHOR]

In this paper, a novel method is proposed for retrieving 3-D topography of the ground surface by using a single-antenna squint-mode airborne synthetic aperture radar (SAR). The main idea of the method is based on the fact that the spatial 3-D location of a target can be found as the intersection of the range sphere, the Doppler cone, and the elevation plane of the antenna pattern. An accurate estimation of the Doppler centroid for each resolution cell is required to realize this method. Experimental results obtained with a Ku-band airborne SAR are presented. The method calls for using a precise calibrated attitude determination unit. [ABSTRACT FROM AUTHOR]

In this paper, we present a quantitative comparison of L- and C-band airborne synthetic aperture radar imagery acquired at like- and cross-polarizations over deformed sea ice under winter conditions. The parameters characterizing the deformation state of the ice are determined at both radar bands and at different polarizations. The separation of deformed and level ice is based on a target detection technique. The threshold is set such that image pixels with intensities equal to or larger than the highest 2% of the level-ice intensity distribution are classified as deformed ice, independent of the radar configuration and ice conditions. Optical imagery of sufficient quality for comparison is available only in a very few cases. To characterize the deformation state, the areal fraction of deformation features and the average distance between these features are evaluated. The values obtained for both parameters are very sensitive to the radar frequency. Aeral fractions are larger, and average distances are smaller at L-band than at C-band because of the much higher intensity contrast between the deformed and level ice at L-band. The differences between polarizations at one radar band are smaller but not always negligible. In comparison to optical images, it was observed that deformed-ice areas can be distinguished from level ice over their whole length and extension at L-band, whereas at C-band, often, only prominent parts are visible. [ABSTRACT FROM AUTHOR]

Inverse synthetic aperture radar (ISAR) images are frequently used in target classification and recognition applications. Some classifiers often require features that can be more easily obtained by extracting scattering centers from ISAR data rather than by reconstructing ISAR images. An available method for scattering center extraction, namely, the CLEAN technique, was proposed in a recent paper by Yang et al. In this paper, an improvement of this CLEAN technique is proposed that introduces a new method for detecting scattering centers. The proposed technique is based on a Gaussianity test, and its effectiveness is first theoretically proven and then tested on real data. Moreover, a comparison with the technique proposed by Yang et al. is shown. [ABSTRACT FROM AUTHOR]

The combination of frequency-modulated continuous-wave (FMCW) technology and synthetic aperture radar (SAR) techniques leads to lightweight cost-effective imaging sensors of high resolution. One limiting factor to the use of FMCW sensors is the well-known presence of nonlinearities in the transmitted signal. This results in contrast- and range-resolution degradation, particularly when the system is intended for high-resolution long-range applications, as it is the case for SAR. This paper presents a novel processing solution, which solves the nonlinearity problem for the whole range profile. Additionally, the conventional stop-and-go approximation used in pulse-radar algorithms is not valid in FMCW SAR applications under certain circumstances. Therefore, the motion within the sweep needs to be taken into account. Analytical development of the FMCW SAR signal model, starting from the deramped signal and without using the stop-and-go approximation, is presented in this paper. The model is then applied to stripmap, spotlight, and single-transmitter/multiple-receiver digital-beamforming SAR operational mode. The proposed algorithms are verified by processing real FMCW SAR data collected with the demonstrator system built at the Delft University of Technology. [ABSTRACT FROM AUTHOR]

This paper describes an unsupervised classifier for polarimetric interferometric synthetic aperture radar (PolInSAR) data. Expectation maximization is used to estimate class parameters that maximize the likelihood of observations in an input data set for a given number of classes. Polarimetric information, in the form of coherency matrices, and interferometric information, in the form of complex coherences, are taken into account. Differences in interferometric phase across different polarization states are explicitly modeled to make the classifier sensitive to the vertical structure of the scene under observation, and the distribution over such phase differences is introduced. The classifier is self-initializing, in that it does not rely on decompositions or thresholds. Classification results obtained for real polarimetric interferometric data are presented and discussed. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of apodization on the statistical properties of synthetic aperture radar (SAR) images and its impact on the capability of extracting information from homogeneous regions of apodized SAR images. The statistical model for the pixel complex amplitude of the apodized image is derived in terms of both probability density function and statistical moments. Knowledge of the statistical properties is then used to develop appropriate schemes for parameter estimation and supervised classification of homogeneous regions with different radar cross sections in apodized SAR images. The performance analysis shows that the new techniques (properly derived for the apodized case) provide information extraction capabilities only slightly worse than those provided by the conventional techniques applied to the nonapodized case. This allows us to conclude that the use of nonlinear apodization yields sidelobe level reduction and main lobe resolution preservation that can be traded with the small losses above. A full characterization of the estimation and classification performance of these new techniques shows that non-linear apodization globally introduces a performance degradation comparable to a reduction of the number of looks of a factor of 1.455 for a homogeneous region. [ABSTRACT FROM AUTHOR]

We describe in detail the theoretical and practical implementation aspects of a simulation for marine radars which can, in particular, be used in multistatic configurations. Since the simulator is intended to deliver pseudoraw signals, it can be used later as a tool to benchmark and improve postprocessing algorithms such as bistatic synthetic aperture radar focusing algorithms and ship wake detection algorithms. The work is divided into two parts. This paper reviews and recalls theoretical prerequisites necessary in implementing such a simulator. Included are the full derivation of the bistatic radar equation from the transmitter to the receiver, accounting also for the transmit-receive time, a description of the sea state phenomenology, a review of the theory of electromagnetic scattering from the sea surface, and the presentation and validation of the method used in the simulation. A companion paper discusses the practical implementation aspects of the simulator as well as an analysis of our results. [ABSTRACT FROM AUTHOR]

Recent analysis of a polarimetric synthetic aperture radar (PolSAR) velocity experiment has shown that azimuth ambiguities can provide useful information for the detection of moving targets with an across-track velocity component in PolSAR images using cross-polarization clutter cancellation. This paper examines this phenomenon using theoretical analysis and simulations and illustrates its application with experimental results. It is shown that, for reciprocal scatterers, the phase difference between HV and VH images is zero, whereas for HV and VH ambiguities, the phase difference is π. For land applications, clutter cancellation is essential for the detection of moving targets in PolSAR images. For maritime applications, it can be used to distinguish images from ambiguities. However, it is important to note that the underlying physical reasons for the performance of clutter cancellation are entirely different from ground moving target indication along-track interferometric SAR. It is also shown that cross-pol clutter cancellation is related to filtering of a double-rate-sampled single-channel SAR signal. [ABSTRACT FROM AUTHOR]

Automated synthetic aperture radar (SAR) stereo correspondence becomes increasingly difficult when imaging high-relief terrain utilizing large stereo crossing-angle geometries because high-relief SAR image features can undergo significant spatial distortions, causing a failure of traditional correlation matching. This paper presents eight coherent spotlight-mode cross-track stereo pairs with stereo crossing angles averaging 93.7° collected over a terrain with slopes greater than 200. These stereo pairs suffer from terrain-induced distortions, resulting in a decrease in complex correlation (coherence) when utilizing scanning- window correlation calculations. The search to maximize complex correlation is changed from a shift-only (disparity) search to a shift-and-scale search using the downhill simplex method. This approach is tested against complex imagery with simulated distortions and then employed on the eight wide-angle stereo collects. The resulting digital terrain maps (DTMs) are compared to ground truth. Using a shift-and-scale correlation approach to estimate disparity, the relative height errors decrease, and the number of reliable DTM posts increase. [ABSTRACT FROM AUTHOR]

This paper studies whether the standard deviation (std) of the Baltic Sea ice backscattering coefficient (σ°) depends on the length of measurement (l). For many kinds of surfaces, especially for a fractal one, this is the case. The study was conducted using one-dimensional C-band helicopter-borne scatterometer data and ENVISAT synthetic aperture radar (SAR) images. The results with both data sets indicate mostly a strong linear dependence between ln(l) and ln(std(σ°)) up to a distance of at least a few kilometers. Based on the analysis of empirical and simulated data (fractal and nonfractal profiles), it seems that sea ice σ° as a function of l is not completely described either by fractional Brownian motion or by a process with a single-scale autocorrelation function. Neither can the values of σ° be regarded as samples from only one probability distribution. The regression coefficients describing the dependency of ln(I) versus ln(std(σ°)) do not discriminate various ice types better than just mean and std of σ°. However, the use of regression coefficients instead of mean and std is preferred due to their scale-invariant comparability with the results of other studies. The dependence of std(σ°) on l should also be taken generally into account in the data analysis, e.g., when constructing classifiers for sea ice SAR data. [ABSTRACT FROM AUTHOR]

The fractional chirp scaling algorithm (FrCSA) is based on the use of the fractional Fourier transform (FrFT) within the chirp scaling algorithm (CSA). In this paper, a closed-form expression for the azimuth FrFT of the FrCSA is mathematically derived and analyzed from the high-resolution synthetic aperture radar imaging point of view. The azimuth-FrFT expression of the FrCSA is compared to that of the classical fast Fourier transform (FFT)-based CSA. As the FFT is a special case of the generalized FrFT, the derived expression is found to be in total agreement with that of the FFT-based CSA when the transformation order is equal to unity; that is the angle of rotation is equal to π/2. [ABSTRACT FROM AUTHOR]

In ultra-wideband synthetic aperture radar (UWB SAR) imaging, scatterers often perform the frequency- and aspect angle-dependent reflectivity characteristic, which is usually neglected in traditional imaging processing. A novel UWB SAR time-frequency representation image formation (TFRIF) is proposed to retrieve the frequency- and aspect angle-dependent information, which is valuable in target detection. Based on the TFRIF, two fusion schemes are studied: pixel level fusion (PLF) and decision level fusion (DLF). Based on the analytical expressions, it is concluded that TFRIF can extract the reflectivity pattern information with high precision and little sacrifice of the spatial resolutions. Quantitative analyses of spatial resolutions and detectability improvement of the proposed fusion schemes are tested on airborne UWB SAR data. The real data results validate the proposed TFRIF and its associated PLF and DLF schemes. [ABSTRACT FROM AUTHOR]

Experimental study is undertaken of the feasibility of forward scattering radar (FSR) and its application to automatic ground target classification. The radar itself, fundamental theoretical analysis, target recognition algorithm and the target's classification subsystem are introduced. For target recognition, the effect of shadow inverse synthetic aperture radar is used. The radar experimental set-up and experimentation results are discussed. For classification, a system is proposed, which extracts features from the radar measurements by using Fourier transform and principle component analysis and uses a nearest neighbour classifier. Speed estimation in FSR is also introduced. By analysing 850 experimentally obtained car signatures, the performance of the system is evaluated and the effectiveness of the system is confirmed. The limitations of the work and its future are also discussed. [ABSTRACT FROM AUTHOR]

To determine whether spaceborne Synthetic Aperture Radar (SAR), specifically fine beam RADARSAT-1 C-band, could be used to provide quantitative data on white mangrove ( Laguncularia racemosa (Gaertner)) forests, backscatter coefficients (σ°) were examined in relation to structural parameter data collected from plots located in a mangrove forest of the Mexican Pacific. Significant coefficients of determination were recorded between the backscatter coefficients and the logarithms of both Leaf Area Index (LAI) and mean stem height at two incident angles for both the dry and wet seasons. The highest coefficients of determination for LAI ( r 2 = 0.60) and mean stem height ( r 2 = 0.72) were observed using the shallower (~40°) and steeper (~47°) incident angles, respectively. No significant relationships were recorded between the backscatter coefficients and either stem density, basal area or mean DBH. Given the results of this investigation, it is recommended that for cloud covered regions, fine beam RADARSAT-1 data could be used by resource managers when they require a quick method for surveying structural damage to mangroves resulting from both natural and anthropogenic causes. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to change detection in multitemporal synthetic aperture radar (SAR) images. The proposed approach exploits a wavelet-based multiscale decomposition of the log-ratio image (obtained by a comparison of the original multitemporal data) aimed at achieving different scales (levels) of representation of the change signal. Each scale is characterized by a different tradeoff between speckle reduction and preservation of geometrical details. For each pixel, a subset of reliable scales is identified on the basis of a local statistic measure applied to scale-dependent log-ratio images. The final change- detection result is obtained according to an adaptive scale-driven fusion algorithm. Experimental results obtained on multitemporal SAR images acquired by the ERS-1 satellite confirm the effective- ness of the proposed approach. [ABSTRACT FROM AUTHOR]

A method for retrieval of leaf area index (LAI) using ENVISAT Advanced Synthetic Aperture Radar vertical/horizontal (VV/HH) polarization ratio was derived for boreal forests. Five alternating polarization single-look complex images of the test site were acquired in summer 2003. The swath range from IS1-1S6 was studied. The VVIHH polarization ratio correlated quite well with the ground truth LAI values. The mean error of the LAI estimates was 0.27 for the test site with mixed forest when data from all images and stands were used without separating between species (or swaths). The respective mean LAI estimation error was 0.3 for Norway spruce (Picea abies (L.) Karst.) and 0.07 for Scots pine (Pinus sylvestris L.) dominated stands. [ABSTRACT FROM AUTHOR]

In this work, multitemporal synthetic aperture radar (SAR) data in conjunction with an electromagnetic (EM) model and a vegetation growth model were used to monitor and explain burn-regrowth events of junco vegetation in a wetland environment. The data used were from Radarsat-1, ENVISAT Advanced Synthetic Aperture Radar (ASAR), and European Remote Sensing 2 (ERS-2) temporal series. The EM model is based on radiative transfer theory and describes junco vegetation as a set of vertical dielectric cylinders on a flat flooded surface. It was used, together with the vegetation growth model, to predict the temporal evolution of the radar response during a burn-regrowth event. This simulation was compared with the ERS-2 vertical (VV) data. It was observed a "bell-shaped" temporal trend that was confirmed by the simulated data with a mean error of 2.5 dB. Additionally, in view of current and future ENVISAT ASAR Alternating Polarization Mode Precision data, the horizontal (HH) SAR temporal response was also simulated giving as a result strong differences between simulated HH and VV temporal trends. These differences are in good agreement with the ones observed between Radarsat-1 HH and ERS-2 VV SAR data acquired at close dates and also with the same differences observed between HH and VV ENVISAT ASAR data. Electromagnetic modeling results provide a sound theoretical interpretation of these observations. [ABSTRACT FROM AUTHOR]

The use of a monostatic radar configuration limits the ability of an inverse synthetic aperture radar (ISAR) system to image targets in certain geometries. By employing multistatic geometries this limitation may be overcome. This paper discusses the emulation of multistatic geometries, via sea surface multipath reflections, using a monostatic system. This application capitalises on the advantages provided by both monostatic and bistatic systems. The possibility of obtaining ISAR images using these emulated multistatic radar configurations is first theoretically discussed and then verified using experimental results. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate Synthetic Aperture Radar (SAR) image segmentation into a given but arbitrary number of gamma homogeneous regions via active contours and level sets. The segmentation of SAR images is a difficult problem due to the presence of speckle which can be modeled as strong, multiplicative noise. The proposed algorithm consists of evolving simple closed planar curves within an explicit correspondence between the interiors of curves and regions of segmentation to minimize a criterion containing a term of conformity of data to a speckle model of noise and a term of regularization. Results are shown on both synthetic and real images. [ABSTRACT FROM AUTHOR]

Bistatic synthetic aperture radars (BSARs) have been the focus of increasing research activity over the last decade. The generalized ambiguity function (GAF) of bistatic SAR is introduced here. First, the GAF for BSAR is represented in the delay-Doppler domain, and is then expanded to the spatial (coordinates) domain. From the GAF, comprehensive knowledge regarding the resolution of BSAR can be extracted, including the range and azimuth resolutions, as well as the area of a resolution cell of BSAR. These general results are also applied to the performance analysis of several particular BSAR geometries, including the space-surface-B SAR (SS-BSAR) system, to demonstrate the potential ability of this newly introduced system. [ABSTRACT FROM AUTHOR]

This letter presents a new approach to actively use radar shadow in order to unwrap and geocode objects that cannot be reconstructed by synthetic aperture radar interferometry alone. This new algorithm may significantly improve phase unwrapping and digital elevation model reconstruction in mountainous topography or in urban areas. The algorithm is explained and examples are given with data from the Shuttle Radar Topography Mission, where shadow is a serious problem in alpine terrain. [ABSTRACT FROM AUTHOR]

The concept of radar satellite constellations, or clusters, for synthetic aperture radar (SAR), moving target indicator (MTI), and other radar modes has been proposed and is currently under research. These constellations form an array that is sparsely populated and irregularly spaced; therefore, traditional matched filtering is inadequate for dealing with the constellation's radiation pattern. To aid in the design, analysis, and signal processing of radar satellite constellations and sparse arrays in general, the characterization of the resolution and ambiguity functions of such systems is investigated. We project the radar's received phase history versus five sensor parameters: time, frequency, and three-dimensional position, into a phase history in terms of two eigensensors that can be interpreted as the dimensions of a two-dimensional synthetic aperture. Then, the synthetic aperture expression is used to derive resolution and the ambiguity function. Simulations are presented to verify the theory. [ABSTRACT FROM AUTHOR]

MIT Lincoln Laboratory is investigating the detection and identification of stationary ground targets in high resolution, fully polarimetric, synthetic aperture radar (SAR) imagery. This article (1) provides a brief description of the Lincoln Laboratory SAR, (2) describes an optimum polarimetric processing technique used to construct minimum-speckle SAR intensity imagery, and (3) presents examples of polarimetrically processed imagery. [ABSTRACT FROM AUTHOR]

Because of its all-weather capability and high resolution, the synthetic aperture radar (SAR) is very effective for remote sensing of the ocean. However, for a moving target such as ocean waves, they affect the SAR images as a phase distortion. This paper considers the orbital motion of the ocean waves. By modeling the waves with an ensemble of the moving points, the SAR image is computed. Previously, the discussions were limited to the case of snapshot observation of the slowly moving ocean waves with a rather long wavelength by a high-speed SAR such as that on a satellite for simplicity of the model. In this paper, this restriction is removed and the estimate and study of the SAR image become possible including a low-speed SAR such as the one on an air-craft and waves with a short wavelength. As a result, it is pointed out that the phase velocity of the ocean waves cannot be neglected in a low-speed SAR so that the wave- length of the SAR image is expanded or compressed and that the SAR image is strongly dependent on the ocean waves and the SAR parameters. [ABSTRACT FROM AUTHOR]

This paper proposes a wavelet-based approach to reducing speckle in synthetic aperture radar (SAR) images. The proposed approach, based on multiresolution analysis with a two-dimensional wavelet transform, aims at smoothing speckle without blurring edges. When an image is transformed by wavelets, edge information appears in detail images. The essence of the method is reducing the power of pixels without edge information in detailed images of each wavelet domain and reconstructing the image by inverse wavelet transform. This approach gives a high ability to smooth speckle and preserve edges in simulations and has been satisfactorily applied to real SAR images. © 1997 Scripta Technica, Inc. Electron Comm Jpn Pt 3, 80(9): 29–36, 1997 [ABSTRACT FROM AUTHOR]

The wavefront curvature error in one stationary bistatic synthetic aperture radar (SAR) image focused via the polar format algorithm (PFA) is analysed and a space-variant filtering method for wavefront curvature correction is proposed. The correction method presented, extends the focused scene size when using the bistatic PFA effectively. Point target simulation validates the filtering method. [ABSTRACT FROM AUTHOR]

A new technique for mitigating Doppler aliasing artifacts in synthetic aperture radar (SAR) imagery is demonstrated. The technique uses continuous-wave (CW) transmission of randomised stepped-frequency waveforms. Subsequent processing places Doppler aliasing artifacts in Doppler filter nulls, effectively removing them from the imagery. Simulated 2-D SAR images illustrate the effectiveness of the technique. [ABSTRACT FROM AUTHOR]