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An algorithm for imaging of targets behind walls is proposed to reduce the wall reflection and enhance the signal-to-clutter ratio. The image formation is based on differential synthetic-aperture-radar image formation employing a continuous-wave radar system. In this approach, instead of using individual backscattered signals, the image is formed by employing the difference signals obtained by subtracting two successive signals along the track. This way, specular reflections are totally eliminated without the need for the knowledge of the wall parameters. This also affects the point target response which is corrected by an integration process. By using backscattered fields from small trihedral corner reflectors behind a poured concrete wall, measured over a frequency band of 1-2.5 GHz, the proposed method is demonstrated. Index Terms--Synthetic aperture imaging, through-wall imaging.

In this paper, the applicability of a procedure for retrieval of vegetation parameters using a coherent scattering model that considers the botanical properties of Sahelian grassland and a stochastic optimization algorithm is studied. This African vegetation is mainly composed of shrubs and grass. Since the coherent scattering model is computationally time-consuming, a simplified empirical model is constructed by fitting of simulation results obtained by the scattering model. Inputs to the empirical model are the sensitive parameters that, for the studied class of vegetation, are the soil moisture content, grass density, and grass moisture content. The model outputs are the polarimetric backscattering coefficients as a function of the incidence angle. Employing the empirical model and a genetic algorithm, a search routine is implemented to estimate the biophysical parameters of the African vegetation from a data set of backscattering coefficients. The estimation of Sahelian-grassland parameters using the set of C-band HH-polarized measured data shows that this procedure achieves good agreement with the ground-truth data. Index Terms--Inversion algorithm, radar remote sensing, Sahelian grassland.

In this paper, a hybrid target--foliage model based on existing electromagnetic techniques is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy at high frequencies. The proposed model is composed of two basic scattering models, one for foliage and the other for the hard targets. The connection between these two models, which accounts for the interaction between the foliage scatterers and the target and vice versa, is accomplished through the application of the reciprocity theorem. Wave penetration through the forest canopy and near-field and far-field scattering from the canopy's constituents is calculated using a coherent discrete scattering model that makes use of realistic tree structures. Calculation of scattering from a hard target illuminated by the reduced incident field and the scattered field of nearby vegetation is carried out using an iterative physical optics (PO) method formulated for fast computation of foliage--target interaction. To reduce the number of iterations, geometrical optics (GO) approximation is initially used for determining the shadowed areas over the hard target when illuminated by individual foliage scatterers. Furthermore, using a scaled measurement system at millimeter-wave frequency, the accuracy of the iterative PO model is demonstrated, employing a complex target that occupies a volume as big as 86[lambda] x 33[lambda] x 20[lambda]. Index Terms--Electromagnetic (EM) scattering, hybrid solution methods.

A hybrid target-foliage model is developed to investigate the scattering behavior of hard targets embedded inside a forest canopy. The proposed model is composed of two existing electromagnetic-scattering models, one for the foliage and the other for the hard targets that are coupled in a computationally efficient manner. The connection between these two models, which accounts for the interaction between the foliage scatterers and the target, is accomplished through the application of Huygens' principle. Wave penetration through the forest canopy and near-field and far-field scattering from its constituents is calculated using a coherent single-scattering theory, which makes use of realistic tree structures. Defining a Huygens' surface enclosing the hard target and calculating the illuminating field (the scattered fields from the nearby vegetation scatterers and reduced incident field), the interaction between the foliage and the hard target is accounted for. Computing the scattered field from target on the Huygens' surface and using a reciprocity theorem target-foliage interaction is captured very efficiently. Calculation of scattering from a hard target is carried out using a finite-difference time-domain (FDTD) technique. For a typical vehicle dimensions, the required time and memory for the FDTD computation and exact field calculation inside the foliage limits the simulation frequency to upper very high frequency (VHF) band. Index Terms--Electromagnetic (EM) scattering, finite-difference time-domain (FDTD) method, hybrid solution methods.

The Shuttle Radar Topography Mission (SRTM) provided data for detailed topographical maps of about 80% of the Earth's land surface. SRTM consisted of single-pass C- and X-band interferometric synthetic aperture radars (INSARs). In order to utilize SRTM data in remote sensing applications the data must be calibrated and validated. This paper presents The University of Michigan's SRTM calibration and validation campaign and our results using recently acquired C-band SRTM data of our calibration sites. An array of calibration targets was deployed with the intention of determining the accuracy of INSAR-derived digital elevation maps. The array spanned one of the X-band swaths and stretched from Toledo, OH to Lansing, MI. Passive and active targets were used. The passive targets included trihedrals and tophats. The locations in latitude, longitude, and elevation of the point targets were determined using differential GPS. We also acquired U.S. Geological Survey (USGS) digital elevation models (DEMs) to use in the calibration and validation work. The SRTM data used in this study are both Principal Investigator Processor (PI) data, which are not the refined final data product, and the ground data processing system (GDPS) data, which are a more refined data product. We report that both datasets for southeastern Michigan exceed the SRTM mission specifications for absolute and relative height errors for our point targets. A more extensive analysis of the SRTM GDPS data indicates that it meets the absolute and relative accuracy requirements even for bare surface areas. In addition, we validate the PI height error files, which are used to provide a statistical characterization of the difference between the SRTM GDPS and USGS DEM heights. The statistical characterization of the GDPS-USGS difference is of interest in forest parameter retrieval algorithms. Index Terms--Digital elevation model (DEM), Shuttle Radar Topography Mission, validation.

Single-scattering theory is shown to be insufficient for the estimation of effective propagation constant in foliage at high microwave and millimeter-wave frequencies. Clusters of broad leaves and needles are treated as a unit scatterer whose ensemble forward scattering is used in Foldy's approximation to estimate attenuation rate in foliage. It is shown that single-scattering approximation overestimates forward scattering as high as 3-4 dB at 35 GHz. Index Terms--Forest scattering, propagation constant, wave propagation.

A full-wave solution for polarimetric scattering from a cluster of randomly oriented three-dimensional lossy dielectric structures above an impedance surface is presented to investigate the importance of multiple scattering. The problem is formulated using an integral equation in conjunction with the exact image representation of dyadic Green's function for the half-space problem. Then, the integral equation is solved for the induced equivalent polarization currents using the method of moments. The accuracy of the numerical code is verified using other existing numerical results and experimental observations. The model is then used to examine the effect of multiple scattering among a cluster of relatively short stems and is shown that multiple scattering significantly affects the cross-polarized backscatter whereas it has a moderate effect on the copolarized backscattering depending on the stem density. Index Terms--Impedance surface, method of moments (MOM), multiple scattering, three-dimensional lossy dielectric structures.

A semi-empirical model of the ensemble-averaged differential Mueller matrix for microwave backscattering from bare soil surfaces is presented. Based on existing scattering models and data sets measured by polarimetric scatterometers and the JPL AirSAR, the parameters of the co-polarized phase-difference probability density function, namely the degree of correlation [alpha] and the co-polarized phase-difference [??], in addition to the backscattering coefficients [[sigma].sup.0.sub.vv] and [[sigma].sup.0.sub.hh] and [[sigma].sup.0.sub.vh], are modeled empirically in terms of the volumetric soil moisture content [m.sub.v] and the surface roughness parameters ks and kl, where k: 2[pi]f/c, s is the rms height and l is the correlation length. Consequently, the ensemble-averaged differential Mueller matrix (or the differential Stokes scattering operator) is specified completely by [[sigma].sup.0.sub.vv], [[sigma].sup.0.sub.hh] [[sigma].sup.0.sub.vh], [alpha], and [zeta] Index Terms--Bare soil surfaces, differential Mueller matrix, microwave backscattering, semi-empirical model.

1998 awards given by the IEEE Geoscience and Remote Sensing Society at IGARSS '98, July 5th, in Seattle, Washington, are detailed. The awards include the Distinguished Achievement Award given to Akira Ishimaru, the Outstanding Service Award given to Wolfgang Keydel, the Transactions Prize Paper Award presented to Christopher S. Ruf, the Symposium Prize Paper Award , the Interactive Session Prize Paper Award, Student Prize Paper Awards, IEEE Fellow Certificates, and the Honorary Life Member Award given to Kiyo Tomiyasu.

This paper considers two specific types of experiments conducted to improve our understanding of radar backscatter from snow-covered ground surfaces. The first experiment involves radar backscatter measurements at C- and X-band of artificial snow of varying depths. The relatively simple target characteristics, combined with an exhaustive ground truth effort, make the results of this experiment especially amenable to comparison with predictions based on theoretical methods for modeling volume-scattering media. It is shown that both conventional and dense-medium radiative transfer models fail to adequately explain the observed results. A direct polarimetric inversion approach is described by which the characteristics of the snow medium are extracted from the measured data. The second type of experiment examined in this study involves diurnal backscatter measurements that were made contemporaneously with detailed measurements of the snow-wetness depth profiles of the observed scene. These data are used to evaluate the capability of a recently proposed algorithm for snow wetness retrieval from polarimetric synthetic aperture radar (SAR) measurements, which has hithertofore been applied only to data from very complex and extended mountainous terrains.

In this paper the theoretical aspects of estimating vegetation parameters from SAR interferometry are presented. In conventional applications of interferometric SAR (INSAR), the phase of the interferogram is used to retrieve the location of the scattering phase center of the target. Although the location of scattering phase center for point targets can be determined very accurately, for a distributed target such as a forest canopy this is not the case. For distributed targets the phase of the interferogram is a random variable which in general is a function of the system and target attributes. To relate the statistics of the interferogram phase to the target attributes, first an equivalence relationship between the two-antenna interferometer system and an equivalent [Delta]k radar system is established. This equivalence relationship provides a general tool to related the frequency correlation function (FCF) of distributed targets, which can conveniently be obtained experimentally, analytically, or numerically, to the phase statistics of the interferogram. An analytical form for the p.d.f. of the interferogram phase is obtained in terms of two independent parameters: 1) [Zeta]: mean phase and 2) [Alpha]: degree of correlation. [Zeta] is proportional to the scattering phase center and [Alpha] is inversely proportional to the uncertainty with which [Zeta] can be estimated. It is shown that [Alpha] is directly related to the FCF of the distributed target which in turn is a function of scattering mechanisms and system parameters. It is also shown that for a uniform closed canopy the extinction and the physical height of the canopy top can be estimated very accurately. Some analytical and numerical simulations are demonstrated.

Accurate determination of spatial soil moisture distribution and monitoring its temporal variation have a significant impact on the outcomes of hydrologic, ecologic, and climatic models. Development of a successful remote sensing instrument for soil moisture relies on the accurate knowledge of the soil dielectric constant ([[Epsilon].sub.soil]) to its moisture content. Two existing methods for measurement of dielectric constant of soil at low and high frequencies are, respectively, the time domain reflectometry and the reflection coefficient measurement using an open-ended coaxial probe. The major shortcoming of these methods is the lack of accurate determination of the imaginary part of [[Epsilon].sub.soil]. In this paper, a microstrip ring resonator is proposed for the accurate measurement of soil dielectric constant. In this technique the microstrip ring resonator is placed in contact with soil medium and the real and imaginary parts of [[Epsilon].sub.soil] are determined from the changes in the resonant frequency and the quality factor of the resonator, respectively. The solution of the electromagnetic problem is obtained using a hybrid approach based on the method of moments solution of the quasistatic formulation in conjunction with experimental data obtained from reference dielectric samples. Also, a simple inversion algorithm for [[Epsilon].sub.soil] = [[Epsilon][prime].sub.r] - j[[Epsilon][double prime].sub.r] based on regression analysis is obtained. It is shown that the wide dynamic range of the measured quantities provides excellent accuracy in the dielectric constant measurement. A prototype microstrip ring resonator at L-band is designed and measurements of soil with different moisture contents are presented and compared with other approaches.

Radar backscatter experiments were conducted at 35 and 95 GHz to measure the response of snow-covered ground to snow depth, liquid water content, and ice crystal size. The measurements included observations over a wide angular range extending between normal incidence and 60 [degrees] for all linear polarization combinations. A numerical radiative transfer model was developed and adapted to fit the experimental observations. Next, the radiative transfer model was exercised over a wide range of conditions and the generated data were used to develop relatively simple semi-empirical expressions that relate the backscattering coefficient (for each linear polarization) to incidence angle, snow depth, crystal size, and liquid water content.

The millimeter-wave (MMW) backscatter response of bare-soil was examined by conducting experimental measurements at 35 and 94 GHz using a truck-mounted polarimetric scatterometer and by developing appropriate models to relate the backscattering coefficient to the soil's surface and volume properties. The experimental measurements were conducted for three soil surfaces with different roughnesses under both dry and wet conditions. The experimental measurements indicate that in general the backscattering coefficient is comprised of a surface scattering component [[Sigma].sup.s] and a volume scattering component [[Sigma].sup.v]. For wet soil conditions, the backscatter is dominated by surface scattering, while for dry conditions both surface and volume scattering are significant, particularly at 94 GHz. Because theoretical surface scattering models were found incapable of predicting the measured backscatter, a semiempirical surface scattering model was developed that relates the surface scattering component of the total backscatter to the roughness parameter ks, where k = 2[Pi]/[Lambda] and s is the rms height, and the dielectric constant of the soil surface. Volume scattering was modeled using radiative transfer theory with the packed soil particles acting as the host material and the air voids as the scattering particles. The combined contribution of surface and volume scattering was found to provide good agreement between the model calculations and the experimental observations.

In this paper, an efficient numerical solution for the scattering problem of inhomogeneous dielectric rough surfaces is presented. The inhomogeneous dielectric random surface represents a bare soil surface and is considered to be comprised of a large number of randomly positioned dielectric humps of different sizes, shapes, and dielectric constants above an impedance surface. Clods with nonuniform moisture content and rocks are modeled by inhomogeneous dielectric humps and the underlying smooth wet soil surface is modeled by an impedance surface. In this technique, an efficient numerical solution for the constituent dielectric humps over an impedance surface is obtained using Green's function derived by the exact image theory in conjunction with the method of moments. The scattered field from a sample of the rough surface is obtained by summing the scattered fields from all the individual humps of the surface coherently ignoring the effect of multiple scattering between the humps. The statistical behavior of the scattering coefficient [Sigma] [degrees] is obtained from the calculation of scattered fields of many different realizations of the surface. Numerical results are presented for several different roughnesses and dielectric constants of the random surfaces. The numerical technique is verified by comparing the numerical solution with the solution based on the small perturbation method and the physical optics model for homogeneous rough surfaces. This technique can be used to study the behavior of scattering coefficient and phase difference statistics of rough soil surfaces for which no analytical solution exists.

The amount of water present in liquid form in a snowpack exercises a strong influence on the radar and radiometric responses of snow. Conventional techniques for measuring the liquid water content m[subscript v] suffer from various shortcomings, which include poor accuracy, long analysis time, poor spatial resolution, and/or cumbersome and inconvenient procedures. This paper describes the development of a hand-held electromagnetic sensor for quick and easy determination of snow liquid water content and density. A novel design of this probe affords several important advantages over existing similar sensors. Among these are improved spatial resolution and accuracy, and reduced sensitivity to interference by objects or media outside the sample volume of the sensor. The sensor actually measures the complex dielectric constant of the snow medium, and the water content and density must be obtained through the use of empirical or semi-empirical relations. To test the suitability of existing models and allow the development of new models, the snow probe was tested against the freezing calorimeter and gravimetric density determinations. From these comparisons, valid models were selected or developed. Based on the use of these models, the following specifications were established for the snow probe: 1) liquid water content measurement accuracy = [+ or -]0.66% in the wetness range from 0 to 10% by volume and 2) wet snow density measurement accuracy = [+ or -]0.05 g/cm[superscript 3] in the density range from 0.1 to 0.6 g/cm[superscript 3].

In preparation for the flight of the Shuttle Imaging Radar-C (SIR-C) on board the Space Shuttle in the spring of 1994, a Level-1 automatic classifier was developed on the basis of polarimetric SAR images acquired by the JPL AirSAR system. The classifier uses L- and C-Band polarimetric SAR measurements of the imaged scene to classify individual pixels into one of four categories: tall vegetation (trees), short vegetation, urban, or bare surface, with the last category encompassing water surfaces, bare soil surfaces, and concrete or asphalt-covered surfaces. The classifier design uses knowledge of the nature of radar backscattering from surfaces and volumes to construct appropriate discriminators in a sequential format. The classifier, which was developed usin training areas in a test site in Northern Michigan, was tested against independent test areas in the same test site and in another site imaged three months earlier. Among all cases and all categories, the classification accuracy ranged between 91% and 100%.

When point calibration targets are used to calibrate a SAR image, the calibration accuracy is governed by two major factors. The first factor stems from the stringent requirement on the radar cross section (RCS) of the point calibration target. To reduce the effect of radar return from the background, the RCS of a point calibration target must be much larger than that of the background. Calibration targets with large RCS require large physical dimension for passive targets or high amplifier gain for active targets, which in practic leads to uncertainty in the nominal RCS of the targets. The second factor is related to the fact that point calibration targets are used to develop a calibration algorithm which is applied to distributed targets. To this end, accurate knowledge of the impulse response (ambiguity function) of the SAR system is required. To evaluate the accuracy of such a calibration process, a cross-calibration experiment was conducted at a test site near Pellston, MI, using the JPL aircraft SAR and the University of Michigan truck-mounted polarimetric scatterometer. Five different types of distributed surfaces, all i the same area, were chosen: three of these were bare surfaces with varying roughnesses, and the other two were covered with vegetation (one with short grass and the other with tall grass). Trihedral corner reflectors were used for calibrating the aircraft SAR, and the UM scatterometer was calibrated using a metallic sphere. The scatterometer data were collected at L and C bands immediately after the aircraft flew over the test site. This paper presents results of the cross calibration between the polarimetric SAR and ground-based polarimetric scatterometer measurements at L and C bands. Comparison of the dat measured by the two radar systems shows that SAR calibration with trihedrals ma lead to unreliable results. It is shown that coherent and incoherent interactio of the ground with a trihedral reflector can significantly alter the expected RCS of an isolated trihedral. A distributed-target calibration technique is introduced and applied to the data with good results.

Existing methods for external calibration of polarimetric synthetic aperture radars (SAR) are all based on point targets with known scattering matrices. The quantity of interest in radar measurement of distributed targets is the backscattering coefficient, which is different from the radar cross section (RCS) formulated for point targets. Therefore, in order to infer the backscattering cross section of a distributed target from a point target rigorously, the polarimetric ambiguity function of the SAR (unknown) is needed for the computation of the effective illumination area. In existing methods the illumination area is approximated by the area of a pixel. The second problem is the uncertainty in the RCS of point calibration targets. The large physical size of the point targets and their interaction with the background produce uncertainties in the measurement of the calibration targets. The third problem with existing methods arises from the application of the calibration algorithm to individual pixels. The measured response of a distributed target by a SAR is the convolution of the actual radar reflectivity of the target with the ambiguity function of the SAR. Thus, the statistics derived from individual pixels is influenced by the ambiguity function and the measurement becomes system dependent. In this paper a calibration algorithm is proposed that circumvents all of the mentioned problems. It is shown that the radar distortion parameters and effective illumination area can be obtained from a homogeneous distributed target with a known differential Mueller matrix. The distortion parameters are then used in an algorithm to provide the calibrated differential Mueller matrix for the other homogeneous targets in the image. This algorithm is tested for the JPL L- and C-band SAR using four different distributed targets measured with polarimetric scatterometers.

The retrieval of scene parameters from polarimetric radar data using an iterative inversion approach is considered in this paper. The theoretical development of a general, model-based iterative algorithm for inversion of polarimetric radar data is presented. Factors relevant to its implementation, such as sensor configuration, algorithm optimization and computational structure are discussed. The algorithm is applied to the specific problem of inverting the vector radiative transfer model for a simplified, representative vegetation canopy consisting of vertical trunks, leaves, and a rough ground surface. The results of this inversion are in excellent agreement with simulated data generated using the radiative transfer model. The convergence properties of the algorithm are evaluated, and it is found that successful convergence is achieved in about 90% to 95% of the cases tested for the implementation used in this work. An error analysis is presented which considers the effect of both systematic and measurement derived errors. Typical error bounds for the current application are approximately + or - 3%, allowing for + or - 0.5 dB accuracy in the measured radar data.

In this paper, the electromagnetic scattering solution for a grass blade with complex cross-section geometry is considered. It is assumed that the blade cross section is electrically small, but its length is large compared to the incident wavelength. In a recent study it has been shown that the scattering solution for such problems, in the form of a polarizability tensor, can be obtained using the low-frequency approximation in conjunction with the method of moments. In addition, the study shows that the relationship between the polarizability tensor of a dielectric cylinder and its dielectric constant can be approximated by a simple algebraic expression. The results of this study are used to show that this algebraic approximation is valid also for cylinders with cross sections the shape of grass blades, providing that proper values are selected for each of three constants appearing in the expression. These constants are dependent on cylinder shape, and if the relationship between the constants and the three parameters describing a grass blade shape can be determined, an algebraic approximation relating polarizability tensor to blade shape, as well as dielectric constant, can be formed. Since the elements of the polarizability tensor are dependent on only these parameters, this algebraic approximation can replace the cumbersome method of moments model. The moment method model is therefore used to generate a small but representative set of polarizability tensor data over the range of values commonly observed in nature. A conjugate gradient method is then implemented to correctly determine the three constants of the algebraic approximation for each blade shape. A third-order polynomial fit to the data is then determined for each constant, thus providing a complete analytic replacement to the numerical (moment method) scattering model. Comparisons of this approximation to the numerical model show an average error of less than 3%.