Engineering topics
Publications and source records attributed to Moghaddam, M..
Several scattering mechanisms contribute to the total radar backscatter cross section measured by the synthetic aperture radar. These are volume scattering, trunk-ground double-bounce scattering, branch-ground double-bounce scattering, and surface scattering. All of these mechanisms are directly related to the dielectric constant of forest components responsible for that mechanism and their moisture.
During several field campaigns in spring and summer of '94, the NASA/JPL air-borne sythetic aperature radar (AIRSAR) collected data over the southern and northern study sites of BOREAS. Among the areas over which radar data were collected was the young jack pine tower site, which is generally characterized as have shot but closely space trees with a dense crown layer.
During several intensive field campaigns in 1993 & 1994, the JPL airborne synthetic aperture radar obtained multifrequency polarimetric radar data over various areas in the Canadian boreal forest designated as primary BOREAS study sites. These were part of a major remote sensing effort geared toward studying the interaction of the forest biome and the atmosphere to identify their role in global change.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
The JPL airborne synthetic aperture radar is a quadpol system operating at three frequencies, which measures the complete stokes matrix of scattering targets and hence their polarization signature.
This paper describes the use of inverse scattering to calculate the equivalent dielectric constant of a random mixture of two-dimensional scatterers.
This paper substantiates earlier findings that radar measurements in the Oregon transect cannot be uniquely related to biomass, and that instead inversion algorithms should be used,.
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This paper discusses the small perturbation model (SPM) used to express backscattering coefficients of the rough surface.
Rough-surface inversion has significant applications in interpretation of SAR data obtained over bare soil surfaces and agricultural lands. Due to the sparsity of data and the large pixel size in SAR applications, it is not feasible to carry out inversions based on numerical scattering models. The alternative is to use parameter estimation techniques based on approximate analytical or empirical models. Hence, there are two issues to be addressed, namely, what model to choose and what estimation algorithm to apply. Here, a small perturbation model (SPM) is used to express the backscattering coefficients of the rough surface in terms of three surface parameters. The algorithm used to estimate these parameters is based on a nonlinear least-squares criterion. The least-squares optimization methods are widely used in estimation theory, but the distinguishing factor for SAR applications is incorporating the stochastic nature of both the unknown parameters and the data into formulation, which will be discussed in detail. The algorithm is tested with synthetic data, and several Newton-type least-squares minimization methods are discussed to compare their convergence characteristics. Finally, the algorithm is applied to multifrequency polarimetric SAR data obtained over some bare soil and agricultural fields. Results will be shown and compared to ground-truth measurements obtained from these areas. The strength of this general approach to inversion of SAR data is that it can be easily modified for use with any scattering model without changing any of the inversion steps. Note also that, for the same reason it is not limited to inversion of rough surfaces, and can be applied to any parameterized scattering process.
The H(sub z)-polarized inverse problem has rarely been studied before due to the complicated way in which the unknown permittivity appears in the wave equation. This problem is equivalent to the acoustic inverse problem with variable density. We have recently reported the solution to the nonlinear variable-permittivity H(sub z)-polarized inverse problem using the Born iterative method. Here, the linear inverse problem is solved for permittivity (epsilon) and permeability (mu) using a different approach which is an extension of the basic ideas of diffraction tomography (DT). The key to solving this problem is to utilize frequency diversity to obtain the required independent measurements. The receivers are assumed to be in the far field of the object, and plane wave incidence is also assumed. It is assumed that the scatterer is weak, so that the Born approximation can be used to arrive at a relationship between the measured pressure field and two terms related to the spatial Fourier transform of the two unknowns, epsilon and mu. The term involving permeability corresponds to monopole scattering and that for permittivity to dipole scattering. Measurements at several frequencies are used and a least squares problem is solved to reconstruct epsilon and mu. It is observed that the low spatial frequencies in the spectra of epsilon and mu produce inaccuracies in the results. Hence, a regularization method is devised to remove this problem. Several results are shown. Low contrast objects for which the above analysis holds are used to show that good reconstructions are obtained for both permittivity and permeability after regularization is applied.
Previously, a scattering model was used to classify SAR data as due to three mechanisms: surface or odd-bounce scattering; double-bounce scattering; and volume scattering. A Bragg rough-surface model was used for odd-bounce scattering, and two reflecting surfaces, as in a dihedral corner reflector, represented the double-bounce scattering mechanism. A random collection of infinitely thin cylinders was used to model the volume scattering contribution. It was assumed that the cylinders are uniformly oriented in all directions. In this work, modifications are made to the above model, which include specifying a preferred orientation for the cylinders representing branches and using thin cylinders of finite thickness as opposed to infinitely thin ones. In the first case, the preferred orientation is represented by a probability density function in the form of a dirac delta function. For the second case, small argument asymptotic expansions of Bessel functions are used to express the volume scattering contributions in terms of quantities containing the average radius of the cylinders. Since in each case the number of unknowns exceeds that of equations, simplifying assumptions are made. The solutions are applied to multifrequency polarimetric SAR data to obtain the new unknowns in addition to the relative contributions of each scattering mechanism. Several results are presented. It is found that the calculated percentage of each mechanism does not change significantly compared to the original model; however, additional information is gained about the scatterers.
The advantages and disadvantages of three different approaches to solving the problem of the radiometric correction of synthetic aperture radar (SAR) images of varying terrain heights are presented. The first approach involves registration of a digital elevation model (DEM) of the terrain to the image, determination of the local elevation and incidence angles, and appropriate radiometric correction. The second approach uses a DEM generated from interferometric SAR data to derive the elevation and incidence angle maps. In the third approach, a monopulse technique is employed to determine the elevation angle only. The relative errors in radiometric correction between these approaches are assessed. Calibration errors are estimated using corner reflectors deployed within some of the scenes imaged by the Jet Propulsion Laboratory airborne SAR (JPL AIRSAR).
To test a forest ecosystem model in the OTTER (Oregon ecosystem research) project, it is desirable to find forest canopy parameters via radar remote sensing measurements. Conventionally, forest biomass, along with quantities such as the leaf area index, drive the model. It is shown that the radar backscatter is not uniquely related to biomass. A sensitivity study is carried out using a forward scattering model to determine the variation of radar cross section as a function of several forest parameters. The results are used to find suitable quantities to recover via radar experiments. A parameter estimation scheme is developed to calculate some preliminary statistical properties of the forest.