Polarimetric Ratio Research Articles

SAR Jamming Suppression by Exploiting Polarized Similarity With Low-Rank and Sparse Matrix Decomposition

Optimal hyper-parameter selection for low-rank and sparse matrix decomposition (LRSMD) in synthetic aperture radar jamming suppression is usually challenging. This letter proposes an effective approach to LRSMD jamming suppression by exploiting the polarized similarity. A polarimetric ratio function is established to straightforwardly determine the rank hyper-parameter. The polarimetric ratio function is defined as the energy ratio of the decomposed low-rank jamming component to the sparse target signal, which is consistent across multiple polarized channels due to the equal jamming gain distinguished from the target polarized scattering. The algorithm optimally exploits the polarized similarity of jamming components to determine the rank hyper-parameter. It provides enhanced robustness and accuracy in SAR jamming removal, confirmed by synthetic experiments.

Calibration Strategy for Compact Polarimetric GNSS-R Instruments

Polarimetric Global Navigation Satellite System - Reflectometry (GNSS-R) is being proposed by different teams as a solution to directly estimate soil moisture. Up to date, two approaches using polarimetric GNSS-R have been proposed to estimate soil moisture, using the ratio between the right-hand and left-hand circularly polarized received signals, and using the ratio between the linear horizontal and vertical components at a set of incidence angles, known as Hybrid Compact Polarimetric (HCP) GNSS-R. In this manuscript, the necessary calibrations of a received HCP GNSS-R signal are presented. The Stokes parameters of the signal are required to compensate all non-idealities. A methodology to calibrate the receiver effects, scene-antenna polarimetric misalignment, Faraday rotation, and transmitter non-idealities is proposed. Finally, the calibration performance is evaluated using several statistical parameters and polarimetric ratio models based on two different soil moisture products. Results show a correlation coefficient increase of 4.7% with respect to the model derived from the Soil Moisture Active Passive (SMAP) soil moisture product, and a 6.5% improvement with respect to the model derived from the European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA-5) monthly average soil moisture product. Furthermore, the proposed calibrations show an unbiased root-mean-square error reduction of 6.3% and 6.8% for the SMAP soil moisture model and the ERA-5 model, respectively. Due to the SMAP antenna and pointing design, SMAP-Reflectometry (SMAP-R) is implicitly insensitive to some of the corrections. More significant corrections should be expected for future polarimetric GNSS-R instruments as European Space Agency (ESA) HydroGNSS.

Tenuous Correlation between Snow Depth or Sea Ice Thickness and C- or X-Band Backscattering in Nunavik Fjords of the Hudson Strait

Radar penetration in brine-wetted snow-covered sea ice is almost nil, yet reports exist of a correlation between snow depth or ice thickness and SAR parameters. This article presents a description of snow depth and first-year sea ice thickness distributions in three fjords of the Hudson Strait and of their tenuous correlation with SAR backscattering in the C- and X-band. Snow depth and ice thickness were directly measured in three fjords of the Hudson Strait from 2015 to 2018 in April or May. Bayesian linear regression analysis was used to investigate their relationship with RADARSAT-2 (C-band) or TerraSAR-X (X-band). Polarimetric ratios and the Cloude–Pottier decomposition parameters were explored along with the HH, HV and VV bands. Linear correlations were generally no higher than 0.3 except for a special case in May 2018. The co-polarization ratio did not perform better than the backscattering coefficients.

The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt

Crop growth is an important parameter to monitor in order to obtain accurate remotely sensed estimates of soil moisture, as well as assessments of crop health, productivity, and quality commonly used in the agricultural industry. The Soil Moisture Active Passive (SMAP) mission has been collecting Global Positioning System (GPS) signals as they reflect off the Earth’s surface since August 2015. The L-band dual-polarization reflection measurements enable studies of the evolution of geophysical parameters during seasonal transitions. In this paper, we examine the sensitivity of SMAP-reflectometry signals to agricultural crop growth related characteristics: crop type, vegetation water content (VWC), crop height, and vegetation opacity (VOP). The study presented here focuses on the United States “Corn Belt,” where an extensive area is planted every year with mostly corn, soybean, and wheat. We explore the potential to generate regularly an alternate source of crop growth information independent of the data currently used in the soil moisture (SM) products developed with the SMAP mission. Our analysis explores the variability of the polarimetric ratio (PR), computed from the peak signals at V- and H-polarization, during the United States Corn Belt crop growing season in 2017. The approach facilitates the understanding of the evolution of the observed surfaces from bare soil to peak growth and the maturation of the crops until harvesting. We investigate the impact of SM on PR for low roughness scenes with low variability and considering each crop type independently. We analyze the sensitivity of PR to the selected crop height, VWC, VOP, and Normalized Differential Vegetation Index (NDVI) reference datasets. Finally, we discuss a possible path towards a retrieval algorithm based on Global Navigation Satellite System-Reflectometry (GNSS-R) measurements that could be used in combination with passive SMAP soil moisture algorithms to correct simultaneously for the VWC and SM effects on the electromagnetic signals.

Soil Moisture Retrieval of Winter Wheat Fields Based on Random Forest Regression Using Quad-Polarimetric SAR Images

Soil moisture has great significance in the researches of hydrology, meteorology and agriculture yield estimation. The quad-polarimetric SAR images can provide a lot of polarimetric features, the significance of the features in surface parameter retrieval have attracted attentions in previous researches with no final conclusions because of the complexity of terrain scattering. In this paper, random forest regression (RFR) is used for both soil moisture retrieval and the importance evaluation of polarimetric features of Radarsat-2 images in winter wheat fields. According to the score of importance, feature selection and combination are done for modelling. We evaluate the retrieval accuracy of models with different feature combinations. The results show that models of important features selected by RFR have RMSE(root mean square error) less than 6% which are better results compared to traditional models; when compared with support vector regression and artifical neural networks, the RFR also shows best retrieval accuracies, which proves that RFR is suitable for soil moisture retrieval and feature selection. The high retrieval accuracies of LBC-CPD(linear backscatter coefficients-Cloude-Pottier decomposition) and LBC-CPR(linear backscatter coefficients-circular polarimetric ratio) indicates these features can improve the retrieval accuracy of soil moisture.

ANALYSIS OF THE TARGET DECOMPOSITION TECHNIQUE ATTRIBUTES AND POLARIMETRIC RATIOS TO DISCRIMINATE LAND USE AND LAND COVER CLASSES OF THE TAPAJÓS REGION

Abstract This study aims to analyze the capability of the target decomposition techniques and the polarimetric ratios applied to the ALOS/PALSAR-2 satellite polarimetric images to discriminate the land use and land cover classes in the Tapajós National Forest region, Pará State. Three full polarimetric ALOS/PALSAR-2, level 1 single look complex scenes were selected to generate the coherence and the covariance matrices to derive the Cloude-Pottier and the Freeman-Durden target decomposition attributes. From the radiometrically calibrated PALSAR-2 images, we generated the backscatter coefficients, the cross polarized ratio (RC; HV/HH), the parallel polarized ratio (RP; VV/HH) and the Radar Forest Degradation Index (RFDI). The images resulting from these polarimetric attributes were processed by the Maximum Likelihood (MAXVER) classifier coupled with the Iterated Conditional Modes (ICM) contextual algorithm. We found that the classifications derived from the target decomposition attributes, mainly from the Cloude-Pottier technique, with a Kappa index of 0.75, presented a significant higher performance than those derived from the RC ratio, RP ratio, and RFDI.

Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching.

The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, even when the patch size has a small enough setting (e.g., 3 × 3 windows). Therefore, this paper proposes an adaptive nonlocal mean filter with shape-adaptive patches matching (ANLM) for PolSAR images. Mainly, the shape-adaptive (SA) matching patches are constructed by combining the polarimetric likelihood ratio test for coherency matrices (PolLRT-CM) and the region growing (RG), which is called PolLRT-CMRG. It is used to distinguish the homogeneous and heterogeneous pixels in textured areas effectively. Then, to enhance the filtering effect, it is necessary to take the adaptive threshold selection of similarity test (Simi-Test) into consideration. The simulated, low spatial resolution SAR580-Convair and high spatial resolution ESAR PolSAR image datasets are selected for experiments. We make a detailed quantitative and qualitative analysis for the filtered results. The experimental results have demonstrated that the proposed ANLM filter has better performance in speckle suppression and detail preservation than that of the traditional local and nonlocal filters.

Multiband modulation spectroscopy for the determination of sex and species of mosquitoes in flight.

We present a dual-wavelength polarimetric measurement method to distinguish species and sexes of disease transmitting mosquitoes in flight. By measuring co- and de-polarized backscattered light at 808 and 1550 nm, the degree of linear polarization, wingbeat frequency, reflectance, spectral ratio and glossiness of mosquitoes can be retrieved. Body and wing contributions to these signals can be separated. Whereas the optical cross section is sensitive to the aspect of observation, thus the heading direction of the insect in flight, we demonstrate that polarimetric- and spectral-band ratios are largely invariant to the aspect of observation. We show that wing glossiness, as well as wing- and body-spectral ratios are particularly efficient in distinguishing Anopheles coluzzii and Anopheles arabiensis, 2 closely related species of malaria vectors. Spectral and polarimetric ratios relate to microstructural and melanization features of the wing and body of these species. We conclude that multiband modulation spectroscopy is a useful expansion of the parameter space that can be used to improve the specificity of entomological lidars.

Spaceborne GNSS-R from the SMAP Mission: First Assessment of Polarimetric Scatterometry over Land and Cryosphere

This work describes the first global scale assessment of a Global Navigation Satellite Systems Reflectometry (GNSS-R) experiment performed on-board the Soil Moisture Active Passive (SMAP) mission for soil moisture and biomass determination. Scattered GPS L2 signals (1227.6 MHz) were collected by the SMAP’s dual-polarization (Horizontal H and Vertical V) radar receiver and then processed on-ground using a known replica of the GPS L2C code. The scattering properties over land are evaluated using the Signal-to-Noise Ratio (SNR), the Polarimetric Ratio (PR), and the width of the waveforms’ trailing and leading edges. These parameters show sensitivity to the effects of the Earth’s topography and Above Ground Biomass (ABG) even over Amazonian and Boreal forests. These effects are shown to be an important factor in precise soil moisture and biomass determination. Additionally, it is found that PR shows sensitivity to soil moisture content over different land cover types. In particular, the following values of the PR are found over: (a) tropical forests ~−1.2 dB; (b) boreal forests ~0.8 dB; (c) Greenland ~2.8 dB; and (d) the Sahara Desert ~3.2 dB.

Sensing soil moisture and vegetation using GNSS-R polarimetric measurement

GNSS-Reflectometry is an efficient tool for remote sensing and plays a key role in several applications. The estimation of soil moisture and vegetation in the land field is attracting widespread interest in hydrology, climatology and carbon cycles. In order to investigate the scattering polarization properties from different types of surface environments, an airborne measurement was performed, equipped with a new 4-channel prototype for collecting the direct, reflected left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP) signals. Both the reflected LHCP and RHCP signals were acquired at the same time by a dual polarization antenna. A data averaging procedure was used to reduce the incoherent part of the received power and two reflected signals were normalized by direct signals obtained from each front-end (FE). Then three polarimetric observables were used to analyze vegetation biomass and soil moisture fluctuations. It was concluded that the polarimetric ratio (PR) is sensitive to soil moisture content (SMC) and considerably independent of roughness and vegetation biomass. The trunk component is confirmed to be the most important factor affecting the amplitude of scattering polarizations. Furthermore, the measurement results showed that the PR variation between different elevation angles was affected by roughness and biomass. The PR variation in forests with big biomass shows the least amount of changes when compared to other geographical environments. The results show another possibility of further geophysical parameter evaluations employing polarimetric applications in GNSS-R.

HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE

ABSTRACT Images of the linear polarizations of synchrotron radiation around active galactic nuclei (AGNs) highlight their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest-resolution polarimetric images of AGNs are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore some extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that only uses bispectrum measurements that are immune to atmospheric phase corruption, with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7 and 3 mm wavelength quasar observations from the VLBA and simulated 1.3 mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm, when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.

GNSS-R Wind-Dependent Polarimetric Signature Over the Ocean

Global Navigation Satellite System-Reflectometry (GNSS-R) is a promising and innovative remote sensing technique. In this letter, an investigation on the polarimetric characteristics of GNSS-R signals is performed. The study is conducted by means of an ad hoc simulator based on a facet approach to approximate a 3-D time-domain generated sea surface. To best mimic a realistic configuration, the simulator uses both recorded GPS and Galileo signals as incident waves. The effect of the incoherent averaging in mitigating the speckle is shown. Finally, a relationship between the wind speed and the polarimetric ratio is analyzed.

First Polarimetric GNSS-R Measurements from a Stratospheric Flight over Boreal Forests

The first-ever dual-frequency multi-constellation Global Navigation Satellite Systems Reflectometry (GNSS-R) polarimetric measurements over boreal forests and lakes from the stratosphere are presented. Data were collected during the European Space Agency (ESA) sponsored Balloon Experiments for University Students (BEXUS) 19 stratospheric balloon experiment using the P(Y) and C/A Reflect Ometer (PYCARO) instrument operated in closed-loop mode. Maps of the polarimetric ratio for L1 and L2 Global Positioning System (GPS) and GLObal Navigation Satellite System (GLONASS), and for E1 Galileo signals are derived from the float phase at 27,000 m height, and the specular points are geolocalized on the Earth’s surface. Polarimetric ratio ( ) maps over boreal forests are shown to be in the range 2–16 dB for the different GNSS codes. This result suggests that the scattering is taking place not only over the soil, but over the different forests elements as well. Additionally to the interpretation of the experimental results a theoretical investigation of the different contributions to the total reflectivity over boreal forests is performed using a bistatic scattering model. The simulated cross- (reflected Left Hand Circular Polarization LHCP) and co-polar (reflected Right Hand Circular Polarization RHCP) reflectivities are evaluated for the soil, the canopy, and the canopy–soil interactions for three different biomass densities: 725 trees/ha, 150 trees/ha and 72 trees/ha. For elevation angles larger than the Brewster angle, it is found that the cross-polar signal is dominant when just single reflections over the forests are evaluated, while in the case of multiple reflections the co-polar signal becomes the largest one. The first-ever dual-frequency multi-constellation Global Navigation Satellite Systems Reflectometry (GNSS-R) polarimetric measurements over boreal forests and lakes from the stratosphere are presented. Data were collected during the European Space Agency (ESA) sponsored Balloon Experiments for University Students (BEXUS) 19 stratospheric balloon experiment using the P(Y) and C/A Reflect Ometer (PYCARO) instrument operated in closed-loop mode. Maps of the polarimetric ratio for L1 and L2 Global Positioning System (GPS) and GLObal Navigation Satellite System (GLONASS), and for E1 Galileo signals are derived from the float phase at 27,000 m height, and the specular points are geolocalized on the Earth’s surface. Polarimetric ratio ( ) maps over boreal forests are shown to be in the range 2–16 dB for the different GNSS codes. This result suggests that the scattering is taking place not only over the soil, but over the different forests elements as well. Additionally to the interpretation of the experimental results a theoretical investigation of the different contributions to the total reflectivity over boreal forests is performed using a bistatic scattering model. The simulated cross- (reflected Left Hand Circular Polarization LHCP) and co-polar (reflected Right Hand Circular Polarization RHCP) reflectivities are evaluated for the soil, the canopy, and the canopy–soil interactions for three different biomass densities: 725 trees/ha, 150 trees/ha and 72 trees/ha. For elevation angles larger than the Brewster angle, it is found that the cross-polar signal is dominant when just single reflections over the forests are evaluated, while in the case of multiple reflections the co-polar signal becomes the largest one.

C-Band Polarimetric Coherences and Ratios for Discriminating Sea Ice Roughness

The rapid decline of sea ice in the Arctic has resulted in a variable sea ice roughness that necessitates improved methods for efficient observation using high-resolution spaceborne radar. The utility of C-band polarimetric backscatter, coherences, and ratios as a discriminator of ice surface roughness is evaluated. An existing one-dimensional backscatter model has been modified to two-dimensions (2D) by considering deviation in the orientation (i.e., the slopes) in azimuth and range direction of surface roughness simultaneously as an improvement in the model. It is shown theoretically that the circular coherence (ρRRLL) decreases exponentially with increasing surface roughness. The crosspolarized coherence (ρHHVH) is found to be less sensitive to surface roughness, whereas the copolarized coherence (ρVVHH) decreases at far-range incidence angles for all ice types. A complete validation of the adapted 2D model using direct measurements of surface roughness is suggested as an avenue for further research.

Distribution of the spectropolarimetric parameter of the moon in the northern part of Ocean Procellarum for a large phase angle

Polarimetric observations of the moon have been carried out at λeff = 0.48 and 0.63 μm using the 50 cm telescope of the Maidanak (Middle Asia) observatory. Imaging has been performed using a Canon-350D camera with a CMOS array and rotating polaroid. The investigation covered the north-western part of the lunar disk comprising the northern part of Ocean Procellarum and obtained the images representing the albedo, polarization degree, color index, and polarimetric color ratio at a phase angle of 96°. It is the first time that the latter parameter has been imaged with a resolution of approximately 1 km. Its pattern has proved to resemble that of the color index, although some important differences can be seen. This shows that spectropolarimetric observations of the moon can give new information on the composition and optical properties of the lunar regolith.

Polarimetric Backscattering Coefficients of Flooded Rice Fields at L- and C-Bands: Measurements, Modeling, and Data Analysis

The polarimetric backscattering coefficients (vv-, hh-, hv-, and vh-polarizations) of a flooded rice field are measured using L- and C-band ground-based polarimetric scatterometers. These measurements were made during the rice growth cycle, i.e., from the transplanting period to the harvest period (May to October 2006), to understand the feasibility of modeling and estimating rice growth. We also collected ground truth data that include fresh and dry biomasses, plant height, leaf area index, and leaf size. To study the incidence angle effect, the scatterometer data were collected at four different incidence angles, i.e., 30deg , 40deg, 50deg, and 60deg. In this paper, we show that the backscattering coefficients of a rice field can accurately be modeled using the radiative transfer theory. We also demonstrate that a polarimetric scatterometer is an effective tool for estimating rice growth. The hh-polarized backscattering coefficient is more sensitive to rice growth than its vv-polarization counterpart. The polarimetric ratio can be used to estimate rice growth accurately.

Microwave bistatic polarization measurements for retrieval of soil moisture using an incidence angle approach

In this paper, the specular scattering (σOHH/VV) behaviour of ten types of plots having different percentage of moisture (mg) and roughness (hrms) has been analysed at various incidence angles with horizontal–horizontal (HH-) and vertical–vertical (VV-) polarizations by an indigenously assembled X-band bistatic scatterometer at frequency of 9.5 GHz. Still, it is very uncertain for minimizing the effect of roughness while retrieving soil moisture. For this purpose, the polarization behaviour of a radar wave has been analysed and a known polarimetric ratio (P = σOHH/σOvv) and proposed polarimetric discrimination ratio have been tested for minimizing the effect of roughness for the retrieval of soil moisture. It was found that PDR has minimum effect of roughness in comparison to P. To avoid the complexity of a moisture retrieval algorithm, we have proposed the incidence angle-based approach to retrieve the soil moisture. The retrieved moisture with the proposed approach is in quite a good agreement with the observed moisture. PDR gives better results than P for retrieval of soil moisture. This type of study and the development of this algorithm will be very helpful in the near future of the Cartwheel satellite system.

Retrieval of wheat chlorophyll by an X-band scatterometer

This paper presents the experimental results of using a scattering coefficient to retrieve chlorophyll at X-band. The observations were carried out in India, during November 1997 to March 1998, by a ground-based X-band scatterometer. The wheat chlorophyll was obtained at a regular interval of 12 days. The scattering coefficient on wheat chlorophyll was measured as a function of the incidence angle and polarization. The scattering coefficient increased as the chlorophyll (chl) increased in the wheat. Chlorophyll is more sensitive for VV-polarization than HH-polarization. There is a significant relationship between chlorophyll and the polarimetric discrimination ratio (D) at an incidence angle of 40°. Using the obtained results, an empirical model for the scattering coefficient is proposed for accessing the chlorophyll of wheat at X-band.

Radar Polarimetric Backscattering Properties of Conical Graupel

Abstract Conical graupel is modeled using sphere-cone-oblate spheroidal shapes for the purpose of computing their backscattering properties at a wavelength of 10 cm in terms of the radar polarimetric observables, reflectivity factors, differential reflectivities and circular depolarization ratios. A shape distribution based on in situ measurements is used together with gamma (m=0, 2) size distributions in the computations; both wet and dry graupel are considered. Significant differences in the radar observables between the wet and dry cases are noted and the effects of canting on the radar observables are considered. The implications of these results on the differentiation of hydrometeor phase with radar are discussed.