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Biomass is a spaceborn polarimetric P-band (435 MHz) synthetic aperture radar (SAR) in a dawn–dusk low Earth orbit. Its principal objective is to measure biomass content and change in all the Earth’s forests. The ionosphere introduces the Faraday rotation on every pulse emitted by low-frequency SAR and scintillations when the pulse traverses a region of plasma irregularities, consequently impacting the quality of the imaging. Some of these effects are due to total electron content (TEC) and its gradients along the propagation path. Therefore, an accurate assessment of the ionospheric morphology and dynamics is necessary to properly understand the impact on image quality, especially in the equatorial and tropical regions. To this scope, we have conducted an in-depth investigation of the significant noise budget introduced by the two crests of the equatorial ionospheric anomaly (EIA) over Brazil and Southeast Asia. This paper is characterized by a novel approach to conceive a SAR-oriented ionospheric assessment, aimed at detecting and identifying spatial and temporal TEC gradients, including scintillation effects and traveling ionospheric disturbances, by means of Global Navigation Satellite Systems ground-based monitoring stations. The novelty of this approach resides in the customization of the information about the impact of the ionosphere on SAR imaging as derived by local dense networks of ground instruments operating during the passes of Biomass spacecraft. The results identify the EIA crests as the regions hosting the bulk of irregularities potentially causing degradation on SAR imaging. Interesting insights about the local characteristics of low-latitudes ionosphere are also highlighted. [ABSTRACT FROM AUTHOR]

The ionospheric propagation path delay is a major error source in synthetic aperture radar (SAR) interferograms and, therefore, has to be estimated and corrected. Various methods can be used to extract different kinds of information about the ionosphere from SAR images, with different accuracies. This paper presents a general technique, based on a Bayesian inverse problem, that combines various information sources in order to increase the estimation accuracy, and thus the correction. A physically realistic fractal modeling of the ionosphere turbulence and a data-based estimation of the model parameters allow the avoidance of arbitrary filtering windows and coefficients. To test the technique, the differential ionospheric phase screen was estimated by combining the split-spectrum method with the azimuth mutual shifts between interferometric pair images. This combination is convenient since it can benefit from the strengths of both sources: range and azimuth variations from the split-spectrum method and small-scale azimuth variations from more sensitive azimuth shifts. Therefore, the two methods can recover the long and short wavelength components of the ionospheric phase screen, respectively. A theoretical comparison between the Faraday rotation method and the split-spectrum method is also reported. For the use in the combination, precedence was then given to the split-spectrum method because of the comparable precision level, lower susceptibility to biases, and wider applicability. Finally, Advanced Land Observing Satellite Phased Array type L-band SAR L-band images are used to show how the combined result is more accurate than that obtained with the simple split-spectrum method. [ABSTRACT FROM PUBLISHER]

Polarimetric target decomposition is the most commonly used method of extracting information from polarimetric synthetic aperture radar (SAR) images. Coherent target decomposition methods are usually suitable for high-resolution images. Recently, Paladini reviewed coherent target decomposition methods and proposed a new approach, lossless and sufficient target decomposition (LSTD), using the special unitary matrix SU(4). However, this method suffers from parameter dependence and commutation problems that could introduce errors in parameter estimation such as an erroneous odd–even bounce ratio. In order to overcome these problems, a new model to decompose the circular polarization scattering vector is proposed. In this paper, the model applies a mapping from SU(4) to SU(6) to simplify the target representation while meaningful parameters, which are independent, can be extracted. Fully polarimetric L-band UAVSAR data are used to validate the proposed method. The most important odd–even bounce ratio parameter is used to compare the estimation accuracy between the proposed method and LSTD. Results show that the proposed method can extract parameters more accurately. [ABSTRACT FROM PUBLISHER]

Compact polarimetric (CP) synthetic aperture radar (SAR) systems are attracting increasing interest as they possess the ability to construct quad-polarimetric information with advantages of simpler system, lower data rate, and wider swath, compared to a fully polarimetric (FP) system. In order to get undistorted polarimetric information, calibration of CP measurements has to be performed. Freeman and Chen both proposed methods for CP SAR calibration using merely calibrators, which require at least three calibrators at a range line and would require many more calibrators when monitoring the change of the system across the swath is necessary. It has been proved that FP SAR calibration methods exploring scattering characteristics of natural distributed targets (DTs) can reduce the requirement of the number of deployed calibrators. However, it is much more complicated in the case of CP SAR calibration, as only two channels of CP measurements are available. This paper proposes a numerical CP calibration method using natural DTs and only one corner reflector (CR) for a reciprocal CP SAR system. The validity of the method for three typical CP modes is confirmed by simulations with Advanced Land Observing Satellite Phased Array L-band SAR data. Through sensitivity analysis, a dihedral at 0 ^\circ is selected as the best CR for the calibration algorithm. [ABSTRACT FROM PUBLISHER]

In this paper, a numerical method optimizer based on covariance matching is proposed for synthetic aperture radar (SAR) polarimetric calibration. The method makes use of the information provided by a distributed target and a corner reflector in order to jointly estimate the system polarimetric distortion parameters and the Faraday rotation. A preliminary analysis is conducted to show the expected accuracy values and to identify the intrinsic ambiguities of the problem. Results from simulations are shown to assess the accuracy and convergence of the method. Finally, tests have been conducted on stack of repeated full polarimetric ALOS PALSAR images to check the stability of the retrieved distortion parameters in a realistic case. [ABSTRACT FROM PUBLISHER]

Spaceborne linearly polarimetric synthetic aperture radar (SAR) provides information about surface properties and scatterer types by measuring the covariances between images formed using orthogonally polarized radio waves. However, ionospheric Faraday rotation (FR) and system calibration errors alter the balance in the polarimetric channels and distort the covariance matrix. Since FR angles are greater at lower radio frequencies, this paper focuses on the Biomass satellite, which is the European Space Agency's 7th Earth Explorer mission and will carry a P-band (435 MHz) polarimetric SAR. Its primary objective is to measure forest biomass density by combining estimates derived from the polarimetric covariance matrix with estimates based on measuring forest height with polarimetric interferometry and exploiting height-biomass allometric relations. The accuracy of four methods for estimating FR from polarimetric SAR is assessed using simulated images of forest with a range of biomass densities and system errors (H/V channel imbalances, antenna crosstalk, and noise) and over a large spread of FR angles. All methods have biases dependent on the FR, the relative phases of the crosstalk components, and the channel imbalance phase. The best performing method estimates FR to better than 5 ° under worst case system errors at all FR angles, so the accuracy of biomass density estimates should not be significantly affected. However, crosstalk phases are predicted to vary greatly across the Biomass antenna beam, and this could potentially cause the FR bias to vary by several degrees across the swath. These effects may occur even for the small values of FR met in L-band data. [ABSTRACT FROM PUBLISHER]

In recent years, significant progress has been made in developing theory and methods for modeling, detecting, and correcting ionospheric effects in low-frequency synthetic aperture radar (SAR) data. While a large number of correction methods have been developed that differ in sensitivity, data needs, and spatiotemporal accuracy, a lack of performance requirements for ionospheric correction has prevented an evaluation of their suitability for operational implementation. Hence, this paper focuses on the development of performance requirements for the correction of ionospheric effects in low-frequency SAR data. The requirements are derived considering the data quality needs of a set of SAR applications and will ensure the SAR data after ionospheric correction to meet calibration specifications and maintain full performance during all ionospheric conditions. The proposed requirements can serve as a benchmark for a performance assessment of ionospheric correction methods and will help define their suitability for operational implementation. Requirements are determined for SAR polarimetry, SAR imaging, SAR interferometry, and ionospheric research. [ABSTRACT FROM AUTHOR]

The quality of polarimetric synthetic aperture radar (PolSAR) imagery and its polarimetric decompositions depends on the accuracy of polarimetric observations of the SAR system and its calibration. Polarization distortions on the polarimetric measurement can be incurred due to nonideal system polarization quality and propagation factors, such as channel imbalance, crosstalk, and Faraday rotation at lower frequencies. All these distortions have varying impacts on different target types as well as different decomposition methods. In this paper, we assess the polarization quality of the PolSAR system in the context of polarimetric imagery analysis and quantify the various effects of polarization distortions on polarization target decompositions. A generic metric is defined to measure the polarization purity of the system. Considering the fact that target decomposition plays an important role in imagery analysis, we apply several widely used decomposition methods to showcase the polarimetric system requirement based on the defined metric. We demonstrate that this metric can be used for radar system design and polarimetric data calibration. [ABSTRACT FROM PUBLISHER]

The third Stokes parameter will be observed from space for the first time at L-band by the Soil Moisture and Ocean Salinity and Aquarius/SAC-D satellites. The correlation between polarizations, which is the source of the third Stokes parameter, is of interest at L-band to measure Faraday rotation and also to indicate novel features of the surface. However, spurious signals (false indication of correlation) can occur in the third Stokes parameter. For example, this happens when the radiometer crosses boundaries associated with a large change in brightness temperature, such as land–water boundaries. In this paper, calculations with the Aquarius radiometer antennas will be used to show that these spurious signals are due to the cross-polarization coupling and large beamwidth associated with realistic L-band antennas in space. [ABSTRACT FROM AUTHOR]

The potential of compact polarimetry (CP) mode at longer wavelengths in a space environment for surface parameter estimation is investigated. CP consists of transmitting a single polarization while receiving two polarizations. At longer wave-lengths, one of the main challenges associated with CP from space is Faraday rotation (FR) estimation and correction. In this paper, an estimation procedure for FR is presented, which relies on the scattering properties of bare surfaces. The selection of the bare surfaces is based on a new parameter, the conformity coefficient computed from CP measurements. This parameter is shown to be FR invariant. Once estimated, the FR can be corrected over the whole image. A simple approximation to δHH° and δVV° based on CP measurements over bare soil surfaces is presented, from which soil moisture can be estimated using the 1995 Dubois et al. algorithm. The results obtained using CP are shown to be in good agreement with those obtained from the standard Dubois et al. algorithm using fully polarimetric data. This implies that, for soil moisture, CP can be used instead of HH and VV dual-polarized measurements. [ABSTRACT FROM AUTHOR]

Yueh proposed a method of using the third Stokes parameter TU to correct brightness temperatures such as Tv and Th for polarization rotation. This paper presents an extended error analysis of the estimation of Tv, Th, and TQ Tv - Th by Yueh's method. In order to carry out the analysis, we first develop a forward model of polarization rotation that accounts for the random nature of thermal radiation, receiver noise, and (to first order) calibration. Analytic formulas are then derived for the bias, standard deviation (STD), and root-mean-square error (RMSE) of estimated TQ, Tv, and Th, as functions of scene and radiometer parameters. These formulas are validated through independent calculation via Monte Carlo simulation. Examination of the formulas reveals that: 1) natural TU from planetary surface radiation, of the magnitude expected on Earth at L-band, has a negligible effect on correction for polarization rotation; 2) RMSE is a function of rotation angle Ω, but the value of Ω that minimizes RMSE is not known prior to instrument fabrication; and 3) if residual calibration errors can be sufficiently reduced via postlaunch calibration, then Yueh's method reduces the error incurred by polarization rotation to negligibility. [ABSTRACT FROM AUTHOR]

Spaceborne microwave observation of subcanopy and subsurface requires the polarimetric synthetic aperture radar (SAR) technology at lower microwave frequencies, such as P-band. However, SAR observation at P-band is remarkably influenced by the Faraday rotation (FR) effect through the ionosphere. An example in this paper illustrates why the measured polarimetric data with FR at P-band cannot be directly applied to terrain surface classification. We further present that the parameters v, H, α, A for terrain surface classification derived from the polarimetric data without FR, which are recovered from the data with FR, can be applied to the surface classification, there is a ±π/2 ambiguity error unresolved. Based on gradual change of the FR degree along a geographical location, a method to eliminate the ±π/2 ambiguity error is designed. Thus, the polarimetric scattering vector and Mueller matrix without FR and ±π/2 ambiguity can be fully inverted from the measured polarimetric data with FR. [ABSTRACT FROM AUTHOR]

Several proposed near-future spaceborne radar missions, such as the Advanced Land Observing Satellite (ALOS) and TerraSAR, will include an L-band instrument. At such low frequencies, the Faraday rotation in the ionosphere, which rotates the polarization plane of the radar signal, becomes an important consideration in instrument design. In this paper, both simple analytic approximations and numerical models are used to derive likely values of Faraday rotation and determine their impact on polarimetric imagery and derived products. One-way rotations exceeding 5° are likely to significantly reduce the accuracy of geophysical parameter recovery, such as forest biomass. On average, Faraday rotation can be neglected at solar minimum, but correction methods are needed at other times of the solar cycle and under disturbed conditions. Methods for implementing such corrections based on estimates of the Faraday rotation and prerotation of the transmitted signal are described. [ABSTRACT FROM AUTHOR]