Comparison of regularized inversion methods in synthetic aperture imaging radiometry

This paper is concerned with the reconstruction of radiometric brightness temperature maps from interferometric measurements. The corresponding inverse problem is often ill-posed unless a regularizing constraint is introduced in order to provide a unique and stable solution. Standard regularizing approaches are compared and illustrated with numerical simulations carried out in reference to the Soil Moisture and Ocean Salinity space mission led by the European Space Agency.     

A resolving matrix approach for synthetic aperture imaging radiometers

Synthetic aperture imaging radiometers (SAIRs) are potential powerful instruments for high-resolution observation of planetary surfaces at low microwave frequencies. This paper deals with the reconstruction of radiometric brightness temperature maps from SAIR interferometric measurements. It is demonstrated that the corresponding inverse problem is not well-posed and must, therefore, be regularized in order to provide a unique and stable solution. A new approach is presented by referring to the notion of modeling operator and to the concept of a resolving matrix of the instrument. To illustrate the theory, numerical simulations are carried out in reference to the Soil Moisture and Ocean Salinity space mission led by the European Space Agency. The results are discussed with emphasis on stability and error analysis.     

Improved Image Reconstruction Algorithms for Aperture Synthesis Radiometers

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission aims at producing global and frequent maps of SMOS and will be launched in 2008. SMOS' single payload is a new type of radiometer called Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) operating at L-band in which brightness temperature images are formed by a Fourier synthesis technique. However, in the alias-free field of view where the brightness temperature images are reconstructed, a bias is present which has been found to be higher for high-contrast brightness temperature scenes (coastlines) and lower for homogeneous scenes (all oceans or lands). This scene-dependent bias will ultimately limit the achievable accuracy of the retrieved geophysical parameters, and it is particularly critical for the retrieval of sea surface salinity. This paper presents a general analysis of the origin of this bias, which is found to be actually due to the different measurement errors in the instrument observables (visibility samples). An improvement of the image reconstruction algorithm is then presented to mitigate it. As compared with the previous algorithm versions, the proposed improved reconstruction algorithm further decomposes the visibility samples into some new terms: ocean and land/iced sea, instead of just the Earth's disk over the sky background. This decomposition aims at further reducing the contrast (high-frequency components) in the differential image and, therefore, minimizes the impact of multiplicative errors, improving the radiometric accuracy. In addition, this approach proves to perform the image reconstruction in part of the alias regions and improves the quality of the reconstruction close to the coastlines.     

Brightness Temperature Map Reconstruction from Dual-Polarimetric Visibilities in Synthetic Aperture Imaging Radiometry

Synthetic aperture imaging radiometers are powerful sensors for high-resolution observations of the Earth at low microwave frequencies. Within this context, the European Space Agency is currently developing the soil moisture and ocean salinity (SMOS) mission devoted to the monitoring of SMOS at global scale from L-band spaceborne radiometric observations obtained with a 2-D interferometer. This paper is concerned with the reconstruction of radiometric brightness temperature maps from interferometric measurements. More exactly, it extends the concept of ldquoband-limited resolving matrixrdquo to the case of the processing of dual-polarimetric data.     

On the estimation of snow depth from microwave radiometricmeasurements

Multiple-channel microwave radiometric measurements made over Alaska at aircraft (near 90 and 183 GHz) and satellite (at 37 and 85 GHz) altitudes are used to study the effect of atmospheric absorption on the estimation of snow depth. The estimation is based on the radiative transfer calculations using an early theoretical model of Mie scattering of single-size particles. It is shown that the radiometric correction for the effect of atmospheric absorption is important even at 37 GHz for a reliable estimation of snow depth. Under a dry atmosphere and based on single-frequency radiometric measurements, the underestimation of snow depth could amount to 50% at 85 GHz and 20-30% at 37 GHz if the effect of atmospheric absorption is not taken into account. The snow depths estimated from the 90-GHz aircraft and 85-GHz satellite measurements are found to be in reasonable agreement. However, there is a discrepancy in the snow depth estimated from the 37-GHz (at both vertical and horizontal polarizations) and 85-GHz satellite measurements     

A Time-Varying Radiometric Bias Correction for the TRMM Microwave Imager

Recent intersatellite radiometric comparisons of the Tropical Rainfall Measurement Mission Microwave Imager (TMI) with polar orbiting satellite radiometer data and modeled clear-sky radiances have uncovered a time-variable radiometric bias in the TMI brightness temperatures. The bias is consistent with a source that generally cools during orbit night and warms during sunlight exposure. The likely primary source has been identified as a slightly emissive parabolic antenna reflector. This paper presents an empirical brightness temperature correction to TMI based on the position around each orbit and the Sun elevation above the orbit plane. The results of radiometric intercomparisons with WindSat and special sensor microwave imager are presented, which demonstrate the effectiveness of the recommended correction approach based on four years of data.     

Penalized-likelihood estimators and noise analysis forrandoms-precorrected PET transmission scans

This paper analyzes and compares image reconstruction methods based on practical approximations to the exact log likelihood of randoms-precorrected positron emission tomography (PET) measurements. The methods apply to both emission and transmission tomography, however, in this paper we focus on transmission tomography. The results of experimental PET transmission scans and variance approximations demonstrate that the shifted Poisson (SP) method avoids the systematic bias of the conventional data-weighted least squares (WLS) method and leads to significantly lower variance than conventional statistical methods based on the log likelihood of the ordinary Poisson (OP) model. We develop covariance approximations to analyze the propagation of noise from attenuation maps into emission images via the attenuation correction factors (ACF's). Empirical pixel and region variances from real transmission data agree closely with the analytical predictions. Both the approximations and the empirical results show that the performance differences between the OP model and SP model are even larger, when considering noise propagation from the transmission images into the final emission images, than the differences in the attenuation maps themselves.     

The analysis of wind exponents retrieved from microwave radar andradiometric measurements

The analysis of the dependence of gravity-capillary spectral density on wind speed is based on near-nadir microwave radiometric measurements and VV scatterometric measurements at view angles 30°-60° from nadir obtained by different investigators in field experiments during the last 25 years. Wind exponents estimated by a symmetric-regression technique for moderate wind speed are consistent both for radiometric and scatterometric measurements. Using Donelan and Pierson's approach, a parameterization of the exponent in the nonlinear dissipation term is derived. The results obtained can be used in model development for the purposes of microwave remote sensing of the ocean     

Microwave radiometric determination of wind speed at the surface of the ocean during BESEX

Microwave radiometric measurements were made at wavelengths ranging from 0.8 to 2.8 cm at altitudes from 0.16 to 11 km under well documented meteorological conditions over the Bering Sea. It is shown that determinations of wind speed at the ocean surface and liquid water content of the clouds may be made from such data. Determinations were made from two simultaneous but independent sets of radiometric measurements. The wind speeds and liquid water contents made from these two sets showed remarkable agreement. Independent estimates of these parameters made from in situ measurements showed reasonable agreement as well.     

Retrievals of low integrated water vapor using MIR and SSM/T-2 measurements

Satellite radiometric measurements at 150, 183.3/spl plusmn/3, and 183.3/spl plusmn/7 GHz have previously been used to retrieve integrated water vapor <1 g/cm/sup 2/ over Antarctica. The effects of the frequency dependence of surface emissivity and the variation of surface temperature on the retrieval, which have not been closely examined in the studies, are analyzed. Using four days of near-concurrent airborne and satellite radiometric measurements, it is shown that the previously derived retrieval algorithm could overestimate or underestimate integrated water vapor by up to 0.1 g/cm/sup 2/, depending on whether the surface emissivity increases or decreases with frequency. The average of the absolute value of the bias for each flight case studied is /spl les/0.04g/cm/sup 2/. Additionally, surface skin temperature is shown to vary substantially over a range from 240-270 K during these four days of measurements; the corresponding effect on the retrieval of integrated water vapor is comparable to that due to frequency dependence on surface emissivity. The quantitative correction needed for this effect is dependent upon the magnitude of integrated water vapor. At high values of integrated water vapor of 0.6-0.8 g/cm/sup 2/, the corrections are as large as 0.1 g/cm/sup 2/ for changes of surface temperature of /spl plusmn/10 K. A simple procedure is implemented to correct for this error, which significantly improves the retrieval. Correction for the frequency dependence of surface emissivity is nontrivial when using currently available satellite measurements; in order to properly correct this effect, an additional channel of measurements, e.g., at 220 GHz, is required.     

Retrieval of precipitable water vapor by the millimeter-waveimaging radiometer in the arctic region during FIRE-ACE

Millimeter-wave radiometric measurements obtained from the NASA ER-2 aircraft over the arctic region on May 20, 1998, were used to estimate precipitable water (PW) in the range⩽0.60 g/cm². The approach is a modified version of the recent work by J. Miao (1998), which utilized the radiometric measurements at 150, 183.3±3, and 183.3±7 GHz of the SSM/T-2 sensor to retrieve PW over the antarctic region. However, Miao has implicitly assumed a surface emissivity that is frequency independent over the 150-183 GHz range. This assumption turns out not to be a good one based on the airborne measurements described below and the errors introduced in the PW estimation were substantial in many cases. It is shown below that four-frequency radiometric measurements in the frequency range of 150-220 GHz provided a robust retrieval of PW, while allowing for a surface emissivity that varied linearly with frequency. The retrieved PW compared favorably with that calculated from rawinsonde data at two widely separated locations. The differences between the retrieved and calculated values are not more than ±0.02 g/cm², which is smaller than errors associated with measurement uncertainty. It is found necessary to account for the double side-band nature of the 183.3 GHz measurements in the radiative transfer calculations for development of the retrieval algorithm. The PW values estimated from the algorithm developed from single side band, 183.3 GHz radiative transfer calculations could be in error by as much as ±0.10 g/cm² . Finally, the effect of surface temperature variations is shown to introduce only a small error in the estimation of PW     

毫米波辐射探测目标亮温的估计

毫米波近感技术是利用物体的毫米波辐射特性探测识别目标，在许多领域有着重要应用。为在毫米波辐射探测中求得精确的真实目标亮温，必须建立天线电磁辐射与环境电磁辐射交会的数学模型，此模型是第一类病态Fredho1m积分方程。寻找适当的方法能得到一个尽可能好的或同精确值相当接近的近似计算方法，为此，本文给出毫米波辐射计目标辐射亮温的估计方法。     

Interband calibration over clouds for POLDER space sensor

The Polarization and Directionality of the Earth's Reflectance (POLDER) spatial polarimeter was onboard the Advanced Earth Observation Satellite (ADEOS) satellite that flew from August 1996 to June 30, 1997. POLDER measured both multidirectional reflectance and polarization in visible and near-infrared spectral bands with a very wide field of view. An accurate absolute radiometric calibration is essential for the scientific exploitation of radiance measurements of the Earth. POLDER inflight radiometric calibration has been performed at the Centre National d'Etudes Spatiales (CNES), French National Space Studies Center, from measurements taken only on well-characterized targets. This paper presents the results of the POLDER in-flight radiometric interband calibration over clouds for channels 443 and 490 nm. The method is based on the comparison of measurements to simulations. Selected measurements correspond to observations over oceans for high, thick convective cumulonimbus and for low, thick stratocumulus. Simulations are calculated using the discrete ordinate computing method. An error budget considers the sensitivity of this calibration method to cloud microphysics, to cloud top altitude, and to aerosols and gaseous loading. Calibration results are discussed for different simulated cloud models     

The date of snow disappearance on the Arctic tundra as determinedfrom satellite, meteorological station and radiometric in situobservations

Satellite-derived snow cover maps for sites in Alaska, Canada, Scandinavia and Siberia were employed to assess the date when snow disappeared on the Arctic tundra and to determine whether the snow has been melting earlier in the spring in recent years. Results show that for three of the four sites there has been a tendency toward earlier snowmelt during the 1980s. In Alaska, the satellite-derived date of snowmelt was compared to the date of snowmelt as observed at the Barrow meteorological station and a site near Barrow where radiometric in situ measurements were made for the last 5 years. The three data sources complement each other even though the satellite site is located 150 km from Barrow. One mechanism which could cause a trend toward earlier snowmelt in Alaska is the deposition of soot and particulates on the snow surface as a result of Arctic haze     

Synergic inversion technique for active and passive microwaveremote sensing of the ocean

A unified approach for combining active and passive microwave measurements for remote sensing applications is described. A synergic inversion technique has been developed and applied to the retrieval of geophysical parameters of the ocean surface and of the atmosphere. It is based on the combination of radiometric and radar measurements at the electromagnetic and cell level and not only on the correction of radar measurements by radiometric measurements, or conversely. Such a combination is performed through a common quantity: the bistatic scattering coefficient of the observed surface. This is used in a direct model to simulate combined measurements from active and passive sensors. It requires a rather complete and accurate calculation of the scattering of microwaves by the rough sea surface     

Radiometric considerations in remote sensing

The need for accurate radiometric data for the verification and use of scene radiation models is emphasized. The radiometric problems associated with reflectance and atmospheric correction field measurements and sensor calibration are reviewed. Estimates are made of the attainable accuracy in each case under favorable conditions. The loss in radiometric accuracy by resampling procedures in digital imagery processing is discussed.     

Radiometric and spectral performance and calibration of the GHz bands of EOS MLS

This paper describes radiometric performance and prelaunch radiometric and spectral calibrations of the GHz component of the Microwave Limb Sounder (MLS) experiment on NASA's Aura spacecraft. Estimated systematic scaling uncertainties (3/spl sigma/) on limb port radiances are /spl sim/0.5% from radiometric calibration and /spl sim/0.5% to /spl sim/1% from spectral calibrations. Operational noise performance is consistent with prelaunch expectations, and in-orbit measurements to date indicate no changes in noise characteristics, and no observable calibration drifts. Spectral baseline has remained stable to /spl sim/20 mK since launch. Refinements to calibrations based on in-flight data are discussed, and radiometric calibration algorithms are described.     

Prelaunch and in-flight radiometric calibration of the Atmospheric Infrared Sounder (AIRS)

With 2378 infrared spectral channels ranging in wavelength from 3.7-15.4 /spl mu/m, the Atmospheric Infrared Sounder (AIRS) represents a quantum leap in spaceborne sounding instruments. Each channel of the AIRS instrument has a well-defined spectral bandshape and must be radiometrically calibrated to standards developed by the National Institute of Standards and Technology. This paper defines the algorithms, methods, and test results of the prelaunch radiometric calibration of the AIRS infrared channels and the in-flight calibration approach. Derivation of the radiometric transfer equations is presented with prelaunch measurements of the radiometric accuracy achieved on measurements of independent datasets.     

Retrieval of hyperthermia-induced temperature distribution from noisy microwave radiometric data

The subcutaneous temperature distribution of a simulated hyperthermic treatment is retrieved from a set of noisy radiometric measurements at six equally spaced frequencies in the range 1.5?6.5 GHz. Temperature profiles reconstructed by the combined use of both the singular value decomposition of the radiometric integral equation and Kalman filtering are shown.