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Geoscience and Remote Sensing, IEEE Transactions on

Issue 5 • Date May 2013

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Displaying Results 1 - 25 of 32
  • [Front cover]

    Page(s): C1
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    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing publication information

    Page(s): C2
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  • Table of contents

    Page(s): 2901 - 2902
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  • Multipixel Retrieval of Structural and Optical Parameters in a 2-D Scene With a Path-Recycling Monte Carlo Forward Model and a New Bayesian Inference Engine

    Page(s): 2903 - 2919
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1217 KB) |  | HTML iconHTML  

    Physics-based retrievals of atmosphere and/or surface properties are generally multi- or hyperspectral in nature; some use multi-angle information as well. Recently, polarization has been added to the available input from sensors and accordingly modeled with vector radiative transfer (RT). At any rate, a single pixel is processed at a time using a forward RT model predicated on 1-D transport theory. Neighboring pixels are sometimes considered but, generally, just to formulate statistical constraints on the inversion based on spatial context. Herein, we demonstrate the power to be harnessed by adding bona fide multipixel techniques to the mix. We use a forward RT model in 2-D, sufficient for this demonstration and easily extended to 3-D, for the response of a single-wavelength imaging sensor. The data, an image, is used to infer position, size, and opacity of an absorbing atmospheric plume somewhere in a deep valley in the presence of partially known/partially unknown aerosol. We first describe the necessary innovation to speed-up forward multidimensional RT. In spite of its reputation for inefficiency, we use a Monte Carlo (MC) technique. However, the adopted scheme is highly accelerated without loss of accuracy by using “recycled” MC paths. This forward model is then put to work in a novel Bayesian inversion adapted to this kind of RT model where it is straightforward to trade precision and efficiency. Retrievals target the plume properties and the specific amount of aerosol. In spite of the limited number of pixels and low signal-to-noise ratio, there is added value for certain nuclear treaty verification applications. View full abstract»

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  • Bayesian Compressive Sensing Approaches for the Reconstruction of Two-Dimensional Sparse Scatterers Under TE Illuminations

    Page(s): 2920 - 2936
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3262 KB) |  | HTML iconHTML  

    In this paper, the reconstruction of sparse scatterers under multiview transverse-electric illumination is dealt with. Starting from a probabilistic formulation of the “inverse source” problem, two Bayesian compressive sensing approaches are introduced. The former is a suitable extension of the single-task method presented earlier for the transverse-magnetic scalar case, while the other exploits an innovative multitask implementation to take into account the relationships among the “contrast currents” at the different probing views. Representative numerical results are discussed to assess, also comparatively, the numerical efficiency, the accuracy, and the robustness of the proposed approaches. View full abstract»

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  • Quantitative Image Recovery From Measured Blind Backscattered Data Using a Globally Convergent Inverse Method

    Page(s): 2937 - 2948
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1246 KB) |  | HTML iconHTML  

    The goal of this paper is to introduce the application of a globally convergent inverse scattering algorithm to estimate dielectric constants of targets using time-resolved backscattering data collected by a U.S. Army Research Laboratory forward-looking radar. The processing of the data was conducted blind, i.e., without any prior knowledge of the targets. The problem is solved by formulating the scattering problem as a coefficient inverse problem for a hyperbolic partial differential equation. The main new feature of this algorithm is its rigorously established global convergence property. Calculated values of dielectric constants are in a good agreement with material properties, which were revealed a posteriori. View full abstract»

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  • Estimating Bedding Orientation From High-Resolution Digital Elevation Models

    Page(s): 2949 - 2959
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1403 KB) |  | HTML iconHTML  

    A high-resolution digital elevation model (DEM), generated from airborne light detection and ranging (LiDAR) remote sensing data, is used here to estimate the 3-D orientation of bedding planes. Methods for enhancement, manual identification and extraction of lineaments, and estimation of best fit planes representing bedding are presented and evaluated for a study area in folded metasedimentary rocks in northeast Tasmania, Australia. Estimated bedding plane dip directions are shown to be accurate and reliable when compared with field-based observations. The same cannot be said for dip angle estimates. It is likely that small errors in the location of a manually digitized lineament will affect dip estimation more than dip direction estimation, particularly for steeply dipping structures. Fold axis orientations calculated from the stereographic analysis of estimated bedding closely correspond to orientations determined from field data. The mean absolute differences $pm$ standard error for 12 of the 14 regularly spaced domains located within the study area were $8.7^{circ} pm 1.2^{circ}$ for the fold plunge and $4.9^{circ} pm 0.9^{circ}$ for the fold trend. The techniques described here for the extraction of bedding plane orientations from high-resolution DEMs complement field-based geological mapping and can assist structural interpretations. View full abstract»

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  • One-Dimensional Mirrored Interferometric Aperture Synthesis: Performances, Simulation, and Experiments

    Page(s): 2960 - 2968
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (516 KB) |  | HTML iconHTML  

    Mirrored interferometric aperture synthesis (MIAS) can reduce the complexity of large IAS systems. In this paper, UV sampling, spatial resolution, sensitivity, and image reconstruction of 1-D MIAS are analyzed, which are not addressed before. Numerical simulation and experiments are carried out to illustrate the performances of MIAS. The results demonstrate the validity of MIAS and the improvement of spatial resolution. View full abstract»

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  • Validation of SMOS L1C and L2 Products and Important Parameters of the Retrieval Algorithm in the Skjern River Catchment, Western Denmark

    Page(s): 2969 - 2985
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1783 KB) |  | HTML iconHTML  

    The Soil Moisture and Ocean Salinity (SMOS) satellite with a passive L-band radiometer monitors surface soil moisture. In addition to soil moisture, vegetation optical thickness $tau_{rm NAD}$ is retrieved (L2 product) from brightness temperatures ( $T_{B}$, L1C product) using an algorithm based on the L-band Microwave Emission of the Biosphere (L-MEB) model with initial guesses on the two parameters (derived from ECMWF products and ECOCLIMAP Leaf Area Index, respectively) and other auxiliary input. This paper presents the validation work carried out in the Skjern River Catchment, Denmark. L1C/L2 data and the most sensitive algorithm parameters were analyzed by network and airborne campaign data collected within one SMOS pixel (44 km diameter). The SMOS retrieval is based on the prevailing low vegetation class. For the L1C comparison, $T_{B}$'s were calculated from in situ soil moisture using L-MEB. Consistent with worldwide findings, the initial/retrieved SMOS soil moisture captures the in situ dynamics well but with significant wet/dry biases and too large amplitudes in case of the latter. While the initial $tau_{rm NAD}$ is in range with an in situ estimate for low agricultural vegetation, the retrieved $tau_{rm NAD}$ is too high with too pronounced temporal variability. A filter based on L2 criteria removed radio frequency interference (RFI) and improved the $R^{2}$ between retrieved and network soil moisture from 0.49 to 0.61, while the bias remained $(-0.092/-!0.087 hbox{m}^{3}/hbox{m}^{3})$ . L- kely error sources include the following: 1) still present RFI; 2) potential link between high retrieved $tau_{rm NAD}$ and other L-MEB parameters, e.g., low roughness parameter $(H_{R})$; 3) $sim$18% lower sand and $sim$8% higher clay fractions while $sim!!0.35 hbox{g/cm}^{3}$ lower bulk density in SMOS algorithm than in situ; and 4) caveats in the Dobson dielectric mixing model implemented in the L-MEB model. A previous study at the Danish validation site had revealed superior performance of the Mironov dielectric mixing model at the 2 $times$ 2 km scale. Studies are ongoing to address the aforementioned issues, and the role of organic surface layers will be investigated. View full abstract»

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  • A New Polarimetric Change Detector in Radar Imagery

    Page(s): 2986 - 3000
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3222 KB) |  | HTML iconHTML  

    In modern society, the anthropogenic influences on ecosystems are central points to understand the evolution of our planet. A polarimetric synthetic aperture radar may have a significant contribution in tackling problems concerning land use change, since such data are available with any-weather conditions. Additionally, the discrimination capability can be enhanced by the polarimetric analysis. Recently, an algorithm able to identify targets scattering an electromagnetic wave with any degree of polarization has been developed, which makes use of a vector rearrangement of the elements of the coherency matrix. In the present work, this target detector is modified to perform change detection between two polarimetric acquisitions, for land use monitoring purposes. Regarding the selection of the detector parameters, a physical rationale is followed, developing a new parameterization of the algebraic space where the detector is defined. As it will be illustrated in the following, this space is 6-D complex with restrictions due to the physical feasibility of the vectors. Specifically, a link between the detector parameters and the angle differences of the eigenvector model is obtained. Moreover, a dual polarimetric version of the change detector is developed, in case quad-polarimetric data are not available. With the purpose of testing the methodology, a variety of data sets were exploited: quad-polarimetric airborne data at L-band (E-SAR), quad-polarimetric satellite data at C-band (Radarsat-2), and dual-polarimetric satellite data at X-band (TerraSAR-X). The algorithm results show agreement with the available information about land changes. Moreover, a comparison with a known change detector based on the maximum likelihood ratio is presented, providing improvements in some conditions. The two methodologies differ in the analysis of the total amplitude of the backscattering, where the proposed algorithm does not take this into consideration. View full abstract»

    Open Access
  • Hierarchical Classification of Moving Vehicles Based on Empirical Mode Decomposition of Micro-Doppler Signatures

    Page(s): 3001 - 3013
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    A novel method is proposed for moving wheeled vehicle and tracked vehicle classification using micro-Doppler features from returned radar signals within short dwell time. In this method, an adaptive analysis technique called Empirical Mode Decomposition (EMD) is utilized to decompose the motion components of moving vehicles, and a hierarchical classification structure using the decomposition results of returned signals is proposed to discriminate the two kinds of vehicles. The first stage of the structure elementarily identifies the tracked vehicle data by checking the existence of its unique feature and a further classification via our proposed features based on EMD is implemented in the second stage by using Support Vector Machine (SVM) classifier. Experimental results based on the simulated data and measured data are presented, including the performance analysis for low signal-to-noise ratio (SNR) case, generalization evaluation for different target circumstances and comparison with some related methods. View full abstract»

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  • General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix

    Page(s): 3014 - 3022
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1169 KB) |  | HTML iconHTML  

    This paper presents a new general four-component scattering power decomposition method by implementing a set of unitary transformations for the polarimetric coherency matrix. There exist nine real independent observation parameters in the 3 $times$ 3 coherency matrix with respect to the second-order statistics of polarimetric information. The proposed method accounts for all observation parameters in the new scheme. It is known that the existing four-component decomposition method reduces the number of observation parameters from nine to eight by rotation of the coherency matrix and that it accounts for six parameters out of eight, leaving two parameters (i.e., the real and imaginary parts of $T_{13}$ component) unaccounted for. By additional special unitary transformation to this rotated coherency matrix, it became possible to reduce the number of independent parameters from eight to seven. After the unitary transformation, the new four-component decomposition is carried out that accounts for all parameters in the coherency matrix, including the remaining $T_{13}$ component. Therefore, the proposed method makes use of full utilization of polarimetric information in the decomposition. The decomposition also employs an extended volume scattering model, which discriminates volume scattering between dipole and dihedral scattering structures caused by the cross-polarized $HV$ component. It is found that the new method enhances the double-bounce scattering contributions over the urban areas compared with those of the existing four-component decomposition, resulting from the full utilization of polarimetric information, which requires highly improved acquisitions of the cross-polarized $HV$ component above the noise floor. View full abstract»

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  • Spatio-Temporal Image Pattern Prediction Method Based on a Physical Model With Time-Varying Optical Flow

    Page(s): 3023 - 3036
    Multimedia
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    This paper proposes an image-based prediction method that can physically predict near-future spatio-temporal image changes using fluid-like image sequences, i.e., dynamic texture, from different image sources such as ground-based radar imagers, satellite sensors, and lightning detectors. Previous alternatives, i.e., tracking radar echo by correlation or thunderstorm identification, tracking, analysis, and nowcasting, employ pattern matching or linear extrapolation of the centroid of an image object to predict the next time image with many tuning model parameters. However, such methods fail to handle the high degree of motion and deformation of fluid-like images, i.e., vortex. To remedy this issue, this paper presents a spatio-temporal prediction method based on a computer vision framework; it employs a physics-based model with time-variant optical flow. Initial local motions from image sequences are estimated by the extended optical flow method, where a locally optimal weighting parameter and a statistically robust function are applied to Horn and Schunck's model. The next time image sequence from the past image sequence is physically predicted by the extended advection equation for image intensities and the Navier–Stokes equation with a continuity equation for varying optical flow over time. For different source images, our method offers no prior knowledge of size, shape, texture, and motion of moving objects. Experiments demonstrate that the proposed prediction method outperforms a previous prediction method with respect to prediction accuracy. View full abstract»

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  • A Novel Technique for the Automatic Detection of Surface Clutter Returns in Radar Sounder Data

    Page(s): 3037 - 3055
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3132 KB) |  | HTML iconHTML  

    One of the most critical problems that affect the analysis of orbiting radar sounder data is the presence of spurious surface clutter returns. These are due to off-nadir echoes related to surface topography which may be detected as (or mask) actual subsurface targets. The detection of such returns is usually carried out manually through a visual comparison between actual radargrams and surface clutter simulations obtained using available digital elevation models (DEMs). This is an inherently subjective and time-consuming task, which may reduce the scientific return of the data. In this paper, we address this problem by proposing a novel technique for the automatic detection of surface clutter returns in radar sounder data. The proposed method is made up of three steps: 1) the simulation of surface clutter returns using available DEMs; 2) the automatic coregistration between radargrams and simulations; and 3) the extraction of surface clutter returns from the coregistered radargrams. The coregistration step is performed in two phases: 1) a coarse registration based on the detection of the first return line on both input radargrams and 2) a fine registration based on B-spline deformation. The proposed technique is robust to radargram geometric deformations (e.g., due to ionospheric effects) and allows the generation of different types of outputs (e.g., coregistered simulations, binary clutter maps, and false-color compositions) that can both greatly support the scientific community in the manual analyses of radar sounder data and drive the development of reliable automatic methods for high level processing. The effectiveness of the proposed method is proven on two data sets acquired on different areas of Mars by the Shallow Radar instrument. View full abstract»

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  • Improved Performance in Horizontal Wind Estimation Using a Spaced Antenna Drift Technique and Signal Processing Approaches

    Page(s): 3056 - 3062
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    The middle and upper atmospheric (MU) radar at Shigaraki, Japan, is an excellent system to carry out observation using a spaced antenna (SA) technique. Over several years, numerous scientific studies were reported using SAs. In most of the studies, a SA is used to derive wind information, and the array is divided in to three segments and is grouped with three or six channels to obtain the baselines in the form of an equilateral triangle. In previous work, the wind had been estimated by the SA up to a maximum height of 10-14 km. In general, a SA-based wind estimation could not give good height coverage due to a smaller aperture being used for received signals. In this paper, the observation has been conducted for full-array transmission and reception of signal with 25 receiver channels of the profiler. The receiver channels are divided into three equal segments to form the baselines suitable for deriving horizontal wind vector components using full correlation analysis (FCA). FCA is considered as a conventional SA technique. The identification of receive channels for grouping and its phase centers was critical to obtain the good correlation value and to determine the velocity. The grouping is repeated with four different orientations of the array group. In each case, the wind velocity is estimated. The horizontal wind vector components obtained from all orientations are averaged to obtain mean horizontal wind vector components. The results are compared with the wind velocity estimated using a Doppler beam swinging (DBS) technique and that observed by the GPS sonde. It is observed that the new approach adopted using spatially distributed array grouping has yielded higher height coverage up to 20 km and in good agreement with the results obtained using DBS and GPS-sonde observations with a temporal resolution of 1.3 min in clear air condition. View full abstract»

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  • Optimum Estimation of Rain Microphysical Parameters From X-Band Dual-Polarization Radar Observables

    Page(s): 3063 - 3076
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1921 KB) |  | HTML iconHTML  

    Modern polarimetric weather radars typically provide reflectivity, differential reflectivity, and specific differential phase shift, which are used in algorithms to estimate the parameters of the rain drop size distribution (DSD), the mean drop shape, and rainfall rate. A new method is presented to minimize the parameterization error using the Rayleigh scattering limit relations multiplied with a rational polynomial function of reflectivity-weighted raindrop diameter to approximate the Mie character of scattering. A statistical relation between the shape parameter of the DSD with the median volume diameter of raindrops is derived by exploiting long-term disdrometer observations. On the basis of this relation, new optimal estimators of rain microphysical parameters and rainfall rate are developed for a wide range of rain DSDs and air temperatures using X-band scattering simulations of polarimetric radar observables. Parameterizations of radar specific path attenuation and backscattering phase shift are also developed, which do not depend on this relation. The methodology can, in principle, be applied to other weather radar frequencies. A numerical sensitivity analysis shows that calibration bias and measurement noise in radar measurements are critical factors for the total error in parameters estimation, despite the low parameterization error (less than 5%). However, for the usual errors of radar calibration and measurement noise (of the order of 1 dB, 0.2 dB, and 0.3 $hbox{deg} hbox{km}^{-1}$ for reflectivity, differential reflectivity, and specific differential propagation phase shift, respectively), the new parameterizations provide a reliable estimation of rain parameters (typically less than 20% error). View full abstract»

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  • MMSE Beam Forming on Fast-Scanning Phased Array Weather Radar

    Page(s): 3077 - 3088
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2481 KB) |  | HTML iconHTML  

    A fast-scanning phased array weather radar (PAWR) with a digital beam forming receiver is under development. It is important in beam forming for weather radar observation with temporally high resolution to form a stable and robust main lobe and adaptively suppress sidelobes with a small number of pulses in order to accurately estimate precipitation profiles (reflectivity, mean Doppler velocity, and spectral width). A minimum mean square error (MMSE) formulation with a power constraint, proposed in this paper, gives us adaptively formed beams that satisfy these demands. The MMSE beam-forming method is compared in various precipitation radar signal simulations with traditional beam-forming methods, Fourier and Capon methods, which have been applied in atmospheric research to observe distributed targets such as precipitation, and it is shown that the MMSE method is appropriate to this fast-scanning PAWR concept. View full abstract»

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  • Radar Backscattering of Lake Ice During Freezing and Thawing Stages Estimated by Ground-Based Scatterometer Experiment and Inversion From Genetic Algorithm

    Page(s): 3089 - 3096
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (903 KB) |  | HTML iconHTML  

    Lake ice under phase transition shows large variation on radar backscattering due to the changes of dielectric constant and roughness of ice surface and thus the transmissivity of microwave into ice body. To study the effects of freezing/thawing of ice on radar backscattering in a short time, we spread water over lake ice and continuously measured radar backscattering by using a ground-based microwave scatterometer system operated in C-band HH polarization. By establishing scattering models and applying inversion from genetic algorithm, radar returns were separated into ice-surface, volume, and ice-bottom scatterings, and the changes in dielectric constant and roughness parameters of ice surface were estimated as well. Immediately after spreading water on ice surface, ice-surface scattering was strongest due to high dielectric constant of surface water while volume and ice-bottom scatterings were very weak due to low microwave transmissivity into ice body. As surface water was being frozen, ice-surface scattering became weak with decreasing dielectric constant while volume and ice-bottom scattering increased due to higher transmissivity into ice body. In a transition stage, when surface water was almost frozen, all three scatterings increased simultaneously. Crystallization of ice produced rougher surface overcoming the decrease in dielectric constant, resulting in the increase of ice-surface scattering, while volume and ice-bottom scattering was continuously increased due to increasing transmissivity. At the end of the experiment, air temperature rose above freezing point, and ice surface thawed again so that ice-surface scattering increased while volume and ice-bottom scattering were decreased. View full abstract»

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  • CW and Pulse–Doppler Radar Processing Based on FPGA for Human Sensing Applications

    Page(s): 3097 - 3107
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2411 KB) |  | HTML iconHTML  

    In this paper, we discuss using field-programmable gate arrays (FPGAs) to process either time- or frequency-domain signals in human sensing radar applications. One example will be given for a continuous-wave (CW) Doppler radar and another for an ultrawideband (UWB) pulse–Doppler (PD) radar. The example for the CW Doppler radar utilizes a novel superheterodyne receiver to suppress low-frequency noise and includes a digital downconverter module implemented in an FPGA. Meanwhile, the UWB PD radar employs a carrier-based transceiver and a novel equivalent time sampling scheme based on FPGA for narrow pulse digitization. Highly integrated compact data acquisition hardware has been implemented and exploited in both radar prototypes. Typically, the CW Doppler radar is a low-cost option for single human activity monitoring, vital sign detection, etc., where target range information is not required. Meanwhile, the UWB PD radar is more advanced in through-wall sensing, multiple-object detection, real-time target tracking, and so on, where a high-resolution range profile is acquired together with a micro-Doppler signature. Design challenges, performance comparison, pros, and cons will be discussed in detail. View full abstract»

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  • A Modified Nonlinear Chirp Scaling Algorithm for Spaceborne/Stationary Bistatic SAR Based on Series Reversion

    Page(s): 3108 - 3118
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2222 KB) |  | HTML iconHTML  

    This paper proposes a method of focusing the bistatic synthetic aperture radar (SAR) (BiSAR) data in spaceborne/stationary configuration. The key problem for imaging is the space variance of Doppler phase. The stationary platform induces additional and different range offsets to the range migration of targets. It causes targets with the same Doppler history, which are determined only by the moving platform, to shift into different bistatic range cells in the echo data. Therefore, the processing is not the same as monostatic SAR imaging which can be fast performed by the uniform matched-filter function in the frequency domain. In this paper, a modified nonlinear chirp scaling (NLCS) algorithm based on series reversion is formulated, which could achieve different range cell migration correction and the equalization of effective range and azimuth frequency modulation rates. The proposed algorithm is validated by simulated and real BiSAR data. In the spaceborne/stationary BiSAR experiment, the YaoGan-1 (an L-band spaceborne SAR system launched by China) is selected as the transmitter, and the stationary receiver is mounted on top of a tall building. The results show that modified NLCS algorithm can effectively focus BiSAR data with serious space variance in spaceborne/stationary configuration. View full abstract»

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  • Time-Reversal-Based Multipath Mitigation Technique for ISAR Images

    Page(s): 3119 - 3138
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4277 KB) |  | HTML iconHTML  

    Inverse synthetic aperture radar (ISAR) is a coherent high-resolution radar technique capable of providing range-Doppler images of non-cooperative targets. Conventional ISAR systems just consider a single reflection of transmitted waveforms from targets. Nevertheless, today's new applications force ISAR systems to work in much more complex scenarios such as urban environments. Consequently, multiple-bounce returns are additionally superposed to direct-scatter echoes. We refer to these as ghost images, since they obscure true target image and lead to poor visual quality, making target detection particularly difficult. By applying time reversal concept to ISAR imaging, it is possible to reduce considerably (or even mitigate) ghosting artifacts, recovering the lost quality due to multipath effects. Nevertheless, before applying this innovative technique, it is essential to estimate the distance between radar and target for each transmitted ramp and for each target scatterer. To that end, a pre-processing algorithm based on detecting the prominent points of a conventional ISAR image corrupted by multipath, followed by a windowing process, is used. Both simulated and real data are used to verify the proposed method. View full abstract»

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  • A Unified Focusing Algorithm for Several Modes of SAR Based on FrFT

    Page(s): 3139 - 3155
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1965 KB) |  | HTML iconHTML  

    Many imaging algorithms for different modes, such as, stripmap synthetic aperture radar (SAR), spotlight SAR, sliding spotlight SAR, and terrain observation by progressive scans (TOPS) SAR, of SAR have been studied. This paper is to obtain a unified focusing algorithm (UFA) for these SAR modes based on fractional Fourier transform. By defining the rotation-center range, the stripmap SAR and spotlight SAR can be treated as special cases of sliding spotlight SAR or TOPS SAR. Then, a parameterized focusing algorithm determined by the rotation-center range is presented. Data of each mode can be focused by utilizing UFA and selecting parameters or rotation angles. Some application aspects of UFA are also analyzed. Simulation and real data results are presented to validate the analysis and the proposed method. View full abstract»

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  • New Applications of Omega-K Algorithm for SAR Data Processing Using Effective Wavelength at High Squint

    Page(s): 3156 - 3169
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (828 KB) |  | HTML iconHTML  

    A novel method to obtain the formulations of the return signals in the 2-D frequency domain for both monostatic and bistatic synthetic aperture radar (SAR) is proposed. In this study, the squinted effective wavelength (SEW) is firstly used, so that the 2-D spectrums can be derived directly from their imaging geometries. For monostatic SAR (MoSAR), the 2-D spectrum is obtained without a lengthy derivation by using the widely-used principle of stationary phase. For the bistatic SAR (BiSAR), based on the assumption that the azimuth time durations of the transmitter and the receiver are the same, two individual SEWs can be derived, as well as the 2-D spectrums that are both concise and of high accuracy. Then, two modified omega-K algorithms based on the two 2-D spectrums are developed to process MoSAR and translational-invariant BiSAR data. Furthermore, as important processing steps of the proposed omega-K algorithms, a modified reference function multiplication and a modified Stolt mapping, which are much more suitable for SAR data processing than the conventional ones, are proposed. Simulations under a wide range of MoSAR and BiSAR system parameters are conducted. Finally, the proposed algorithms are applied to the analysis of acquired data and the results confirm not only the validity of the derived 2-D spectrums for both MoSAR and BiSAR but also the effectiveness of the proposed method. View full abstract»

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  • On Semiparametric Clutter Estimation for Ship Detection in Synthetic Aperture Radar Images

    Page(s): 3170 - 3180
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    The statistical behavior of the sea clutter in synthetic aperture radar (SAR) images is characterized by both the marginal distribution and the spatial correlation. However, simultaneous modeling of the joint information remains a difficult job because of the non-Gaussian clutter nature. In this paper, a semiparametric approach is proposed for addressing this problem. First, we investigate the applicability of the nonparametric kernel density estimator (KDE) for estimating the marginal distribution of the SAR clutter and show that the KDE is most applicable in the log-intensity domain. Second, we propose to estimate the underlying spatial correlation structure with a copula approach and show that the Gaussian copula is a sufficiently accurate model. Consequently, the KDE, together with the Gaussian copula, offers a full characterization of the joint probability distribution, based on which a quadratic detector of null distribution governed by the well-known chi-squared law can be conveniently designed for constant false alarm rate detection. In the experiment, results with both simulated and real SAR data demonstrate that, compared with the single-point detector using only the marginal distribution, the proposed method, which incorporates spatial correlation, significantly improves the detection performance with regard to either the receiver-operating-characteristic curve or detected target pixels. The tradeoff, however, lies in a loss of false alarm rate control resulting from increased uncertainty in estimating higher dimensional distributions. View full abstract»

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  • Demonstration of SAR Distortion Correction Using a Ground-Based Multichannel SAR Test Bed

    Page(s): 3181 - 3190
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    In this paper, a ground-based phased-array radar is used to investigate the ability of a multichannel synthetic aperture radar (MSAR) to produce high-fidelity images of dynamic ocean scenes by correcting the distortions caused by the motion of the water surface itself. The ground-based system, the Naval Research Laboratory Focused Phased Array Imaging Radar (FOPAIR), mimics an MSAR with multiple apertures arrayed in the flight direction by rapidly and repeatedly scanning across a linear array of 64 antenna elements. This generates a virtually unlimited time stack of coherent images in the same way that an airborne MSAR generates multiple images as the antennas fly past the scene. By manipulating a single FOPAIR data set, both undistorted “benchmark” imagery and distorted images corresponding to an airborne MSAR can be generated. More significantly, the time stack of emulated MSAR images can be processed further using the velocity synthetic aperture radar (VSAR) technique to significantly reduce the well-known but seemingly unavoidable distortions caused by surface wave motion. In this paper, VSAR is demonstrated experimentally for the first time using FOPAIR imagery of a small boat. MSAR systems with a wide range of aperture numbers are emulated, including the special case of a two-aperture system, commonly known as an along-track interferometric SAR. The results emphasize that VSAR processing does not require a long surface coherence time to produce fine-resolution imagery, unlike a single-channel SAR. The results also illustrate some limitations of VSAR as a means to measure velocity and produce high-fidelity imagery of dynamic ocean scenes. View full abstract»

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Aims & Scope

 

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

 

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Editor-in-Chief
Antonio J. Plaza
University of Extremadura