Dual-polarization Measurements Research Articles

Recent developments in tornado theory and observations.

This article critically reviews research on tornado theory and observations over the last decade. From the theoretical standpoint, the major advances have come through improved numerical-simulation models of supercell convective storms, which contain the tornado's parent circulation. These simulations are carried out on a large domain (to capture the supercell's circulation system), but with high grid resolution and improved representations of sub-grid physics (to capture the tornado). These simulations offer new insights into how and why tornadoes form in some supercells, but not others. Observational advances have come through technological improvements of mobile Doppler radars capable of rapid scanning and dual-polarization measurements, which offer a much more accurate view of tornado formation, tornado structure, and the tornado's place within its parent supercell.

Array Configuration Design for Mirrored Aperture Synthesis Radiometers Based on Dual-Polarization Measurements

In mirrored aperture synthesis (MAS), the antenna array determines the rank of the transformation matrix connecting the cross-correlations to the cosine visibilities. However, the transformation matrix is rank-deficient, resulting in errors in the reconstructed brightness temperature (BT) image. In this paper, the signal propagations for the vertically polarized wave and horizontally polarized wave are analyzed. Then, the optimization model of the antenna array based on dual-polarization is established. The optimal array configurations are presented, with the corresponding transformation matrices being almost column full ranks. Simulation results demonstrate the validity of the proposed optimization model.

Correlation-based transceiver in-phase/ quadrature skew in-field calibration in dual-polarization coherent optical transmission system.

In this paper, we propose a novel transceiver in-phase/quadrature (I/Q) skew in-field calibration scheme with correlation-based method for the dual-polarization coherent optical system. Simultaneous dual-polarization calibration of transceiver I/Q skews after fiber transmission is experimentally performed. Rx/Tx correlation-based skew estimations (CBSEs) are proposed to accurately estimate the transceiver I/Q skews with dual-polarization OFDM signal. By simulation, the robustness of the Rx/Tx CBSEs is investigated against various transceiver I/Q imbalances and channel impairments including carrier frequency offset (CFO), phase noise (PN), and chromatic dispersion (CD). The simultaneous measurement of large transceiver skews is studied within a range of ±128 ps. The bit error rate (BER) improvement brought by the CBSEs is studied in 80 km single-mode fiber (SMF) transmissions under various Rx/Tx skews. In the experiments, the Rx/Tx skew is measured in the range of 1 to 128 ps w/ and w/o the presence of 5 ps Tx/Rx skew. Simultaneous dual-polarization measurements are performed with the X/Y polarization Tx/Rx skews set to 2.5 ps, 5 ps, 7.5 ps and 10 ps, respectively. The measurement errors are within ±0.2 ps. The 80 km SMF dual-polarization transmission after in-field calibration for inter-data center interconnection (inter-DCI) is implemented, with a data rate of 400 Gb/s for both 16QAM and 32QAM modulation formats.

On the determination of ionospheric electron density profiles using multi-frequency riometry

Abstract. Radio wave absorption in the ionosphere is a function of electron density, collision frequency, radio wave polarisation, magnetic field and radio wave frequency. Several studies have used multi-frequency measurements of cosmic radio noise absorption to determine electron density profiles. Using the framework of statistical inverse problems, we investigated if an electron density altitude profile can be determined by using multi-frequency, dual-polarisation measurements. It was found that the altitude profile cannot be uniquely determined from a “complete” measurement of radio wave absorption for all frequencies and two polarisation modes. This implies that accurate electron density profile measurements cannot be ascertained using multi-frequency riometer data alone and that the reconstruction requires a strong additional a priori assumption of the electron density profile, such as a parameterised model for the ionisation source. Nevertheless, the spectral index of the absorption could be used to determine if there is a significant component of hard precipitation that ionises the lower part of the D region, but it is not possible to infer the altitude distribution uniquely with this technique alone.

A machine learning approach for classifying bird and insect radar echoes with S-band Polarimetric Weather Radar

AbstractThe S-bandWSR-88D weather radar is sensitive enough to observe biological scatterers like birds and insects. However, their non-spherical shapes and frequent collocation in the radar resolution volume create challenges in identifying their echoes. We propose a method of extracting bird (or insect) features by coherently averaging dual polarization measurements from multiple radar scans, containing bird (insect) migration. Additional features are also computed to capture aspect and range dependence, and the variation of these echoes over local regions. Next, ridge classifier and decision tree machine learning algorithms are trained, first only with the averaged dual pol inputs and then different combinations of the remaining features are added. The performance of all models for both methods, are analyzed using metrics computed from the test data. Further studies on different patterns of birds/insects, including roosting birds, bird migration and insect migration cases, are used to further investigate the generality of our models. Overall, the ridge classifier using only dual polarization variables was found to perform consistently well across all these tests. Our recommendation is that this classifier can be used operationally on the US Next-Generation Radars (NEXRAD), as a first step in classifying biological echoes. It would be used in conjunction with the existing Hydrometeor Classification Algorithm (HCA), where the HCA would first separate biological from non-biological echoes, then our algorithm would be applied to further separate biological echoes into birds and insects. To the best of our knowledge, this study is the first to train a machine learning classifier that is capable of detecting diverse patterns of bird and insect echoes, based on dual polarization variables at each range gate.

Accurate near-field millimeter-wave imaging of concave objects using circular polarizations.

Millimeter-wave (MMW) imaging is becoming an important option in many sensing applications. However, the resulting images are often plagued with artifacts caused by complex target scenarios such as concave structures, hampering applications where precise recognition is emphasized. It has been shown that existing imaging techniques can effectively resolve this issue by considering the multi-reflection propagation process in the forward model of the inverse problem. But the accuracy of such method still depends on the precise separation of reflected signals exhibiting different number of interactions with the target surfaces. In this article, an improved imaging technique based on circular polarizations is proposed for accurate imaging of concave objects. By utilizing circular polarized measurements, the received signal can be divided into odd and even number of reflection times. Then, an iterative reconstruction technique is introduced to automatically separate signal components and reconstruct precise contours of the concave surfaces. Furthermore, a strict observation angle boundary model is derived based on methods of the stationary phase to correct the image deformation of edges existing in previous algorithms. Both numerical and experimental results synthesized from 6∼18 GHz dual-polarized measurements are used to demonstrate the improved accuracy and automation of the proposed method.

Radar and ground-level measurements of precipitation collected by the École Polytechnique Fédérale de Lausanne during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games

Abstract. This article describes a 4-month dataset of precipitation and cloud measurements collected during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018). This paper aims to describe the data collected by the Environmental Remote Sensing Laboratory of the École Polytechnique Fédérale de Lausanne. The dataset includes observations from an X-band dual-polarisation Doppler radar, a W-band Doppler cloud profiler, a multi-angle snowflake camera and a two-dimensional video disdrometer (https://doi.org/10.1594/PANGAEA.918315, Gehring et al., 2020a). Classifications of hydrometeor types derived from dual-polarisation measurements and snowflake photographs are presented. The dataset covers the period from 15 November 2017 to 18 March 2018 and features nine precipitation events with a total accumulation of 195 mm of equivalent liquid precipitation. This represents 85 % of the climatological accumulation over this period. To illustrate the available data, measurements corresponding to the four precipitation events with the largest accumulation are presented. The synoptic situations of these events were contrasted and influenced the precipitation type and accumulation. The hydrometeor classifications reveal that aggregate snowflakes were dominant and that some events featured significant riming. The combination of dual-polarisation variables and high-resolution Doppler spectra with ground-level snowflake images makes this dataset particularly suited to study snowfall microphysics in a region where such measurements were not available before.

Dual polarization measurements of MWA beampatterns at 137 MHz

ABSTRACT The wide adoption of low-frequency radio interferometers as a tool for deeper and higher resolution astronomical observations has revolutionized radio astronomy. Despite their construction from static, relatively simple dipoles, the sheer number of distinct elements introduces new, complicated instrumental effects. Their necessary remote locations exacerbate failure rates, while electronic interactions between the many adjacent receiving elements can lead to non-trivial instrumental effects. The Murchison Widefield Array (MWA) employs phased array antenna elements (tiles), which improve collecting area at the expense of complex beam shapes. Advanced electromagnetic simulations have produced the fully embedded element (FEE) simulated beam model which has been highly successful in describing the ideal beam response of MWA antennas. This work focuses on the relatively unexplored aspect of various in-situ, environmental perturbations to beam models and represents the first large-scale, in-situ, all-sky measurement of MWA beam shapes at multiple polarizations and pointings. Our satellite based beam measurement approach enables all-sky beam response measurements with a dynamic range of ∼50 dB, at 137 MHz.

Sensitivity Analysis of Bistatic Scattering for Soil Moisture Retrieval

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems.

A Machine Learning System for Precipitation Estimation Using Satellite and Ground Radar Network Observations

Space-based precipitation products are often used for regional and/or global hydrologic modeling and climate studies. A number of precipitation products at multiple space and time scales have been developed based on satellite observations. However, their accuracy is limited due to the restrictions on spatiotemporal sampling of the satellite sensors and the applied parametric retrieval algorithms. Similarly, a ground-based weather radar is widely used for quantitative precipitation estimation (QPE), especially after the implementation of dual-polarization capability and urban scale deployment of high-resolution X-band radar networks. Ground-based radars are often used for the validation of various spaceborne measurements and products. This article introduces a novel machine learning-based data fusion framework to improve the satellite-based precipitation retrievals by incorporating dual-polarization measurements from a ground radar network. The prototype architecture of this fusion system is detailed. In particular, a deep learning multi-layer perceptron (MLP) model is designed to produce the rainfall estimates using the geostationary satellite infrared (IR) data and low earth orbit satellite passive microwave (PMW)-based retrievals as inputs. The high-quality rainfall products from the ground radar network are used as the target labels to train this MLP model. An urban scale demonstration study over the Dallas-Fort Worth (DFW) metroplex is presented. In addition, the Climate Prediction Center morphing technique (i.e., CMORPH) is adopted for preprocessing of the satellite observations. Rainfall products from this deep learning system are evaluated using the standard CMORPH products. The results show that the proposed data fusion framework can be used for generating accurate precipitation estimates and could be considered as an alternative tool for developing future satellite retrieval algorithms.

Subsurface Radiolocation Tomography of Cables under Dual-Polarization Probing

It is proposed to use the tomographic approach to the problem of detecting and imaging concealed utility networks. This approach is based on generating the three-dimensional radio images of the space being explored from the results of measuring its location wave projections in a dual-polarization measurement mode. The problem is solved by focusing radiation first on the “air–dielectric” interface and then inside the dielectric. Experimental data processing results and reconstructed threedimensional radio tomograms are provided for a “twisted pair” cable and a fiber-optic cable with no metallic inclusions. The results confirm the operability of the approach.

Spherical Near-Field Scanning With Pointwise Probe Correction

Spherical wave expansion algorithms based on matrix inversion are flexible. They allow arbitrary sampling schemes and higher order probe correction. However, the probe correction technique assumes, up until now, the same measurement probe at every measurement point. This is a limitation, especially for dual-polarized measurement probes and multiprobe measurement systems. In this communication, a spherical near-field (SNF) far-field transformation procedure, including pointwise probe correction, is presented. For a measurement sphere with constant radius, the additional calculation time is small. Furthermore, varying but known measurement distances can be corrected using the same technique. The procedure is tested with a dual-polarized SNF measurement and a simulated measurement with varying measurement distances.

Insights into riming and aggregation processes as revealed by aircraft, radar, and disdrometer observations for a 27 April 2011 widespread precipitation event

AbstractThis study presents aircraft spiral ascent and descent observations intercepting a transition to riming processes during widespread stratiform precipitation. The sequence is documented using collocated scanning and profiling radar, including longer‐wavelength dual polarization measurements and shorter‐wavelength Doppler spectra. Riming regions are supported using aircraft measurements recording elevated liquid water concentrations, spherical particle shapes, and saturation with respect to water. Profiling cloud radar observations indicate riming regions during the event as having increasing particle fall speeds, rapid time‐height changes, and bimodalities in Doppler spectra. These particular riming signatures are coupled to scanning dual polarization radar observations of higher differential reflectivity (ZDR) aloft. Reduced melting layer enhancements and delayed radar bright‐band signatures in the column are also observed during riming periods, most notably with the profiling radar observations. The bimodal cloud radar Doppler spectra captured near riming zones indicate two time‐height spectral ice peaks, one rimed particle peak, and one peak associated with pristine ice needle generation and/or growth between −4°C and −7°C also sampled by aircraft probes. This pristine needle population gives a partial explanation for the enhanced ZDR we observe near this rimed particle region. The riming signatures aloft and radar measurements within the melting level are weakly lag correlated (r~0.6) with smaller median drop sizes at the surface, as compared with later times when aggregation of larger particle sizes was believed dominant.

Polarization and Effects on Hidden Node/Shadowing Margin for TVWS

Dual polarized measurements comparing the received power of a line of sight broadcast signal in the ultra-high frequency band with received power in suburban streets and indoors including high rise buildings are presented in this paper. Both the co-polarized and cross-polarized fades are therefore measured in the different locations. Their purpose is twofold: 1) to identify the importance of using polarization when considering hidden node margins in spectrum sensing of television white spaces and 2) to indicate how polarization can be beneficial in improving the shadowing margin to increase the path loss from the secondary to primary user and thus further protect digital terrestrial television receivers from harmful interference. The impact of polarization in open environments with low clutter or near windows inside high rise buildings is more significant than in densely cluttered spaces experiencing strong multipath.

Classification and correction of the bright band using an operational C-band polarimetric radar

Summary The Bright Band (BB) is a region of enhanced reflectivity in weather radar scans associated with frozen hydrometeors forming a liquid coating as they fall through the melting layer. This enhancement can cause the radar to overestimate precipitation quantities at the surface. The main objective of this study is to develop a hydrometeor classification algorithm that can use dual-polarisation measurements as the only input to classify the BB area. An effort has been made to replicate the current UK Met Office operational method for BB classification. This involves the use of Numerical Weather Prediction outputs of freezing level heights with an assumption of a constant BB thickness. Vertical Profiles of Reflectivity (VPR) can then be used to correct for the reflectivity enhancement. A mean apparent VPR computed from reflectivity measurements at multiple elevation angles is compared to two idealised VPR methods. For validation the corrected 1.5° elevation scans are compared to surface rain gauge observations and lower elevation scans over the course of 7 events. The hydrometeor classification methods showed the greatest error reductions, with the freezing level forecast method performing well when the BB thickness was within 700 m, but poorly when there was more variation. Overall the idealised VPRs allowed for the greatest BB corrections in comparison to the mean profile.

A Hybrid Dual-Polarization GPR System for Detection of Linear Objects

To circumvent the polarization sensitivity of ground penetrating radar (GPR) in detecting a linear object, we propose a simple hybrid dual-polarization GPR system consisting of a circularly polarized spiral antenna for transmit and two orthogonally oriented Vivaldi antennas for receiving two linear polarizations. The hybrid combination of a spiral antenna with two Vivaldi antennas is demonstrated to operate in an ultrawideband, to have small antenna dispersion, and to possess favorable antenna isolation. The improved performance of the proposed GPR system over a conventional single-polarized one in detecting linear subsurface objects is indicated by a laboratory experiment in a sandpit. Moreover, the proposed system enables fully coherent dual-polarization measurements with a single transmitter.

English

Antennas are one of the most important parts of a communication chain. They are used for both communication and calibration purposes. Antenna measurement techniques involving near-field probes have been a recently developing area. New developments in probe technologies have enabled near-field probes with much larger bandwidth. The objective of this Master's Thesis is to design, simulate and fabricate a dual polarized wideband inverted quad ridged shape horn antenna which can be used as measurement probe for near field measurements. Typical probes like Open Ended Waveguides, dipole antenna probes etc are bulky in mobile communication frequency bands. In addition they are narrow band probes. The inverted quad-ridged horn antenna probe not only provides measurement in the much wider range but also provides dual-polarization measurement thus enabling antenna developers to measure UWB, UHF, VHF antennas more precisely and at lower cost. The antenna is designed to meet the characteristics such as high gain, light weight, linearly polarized with suppressed side lobes for near-field measurement applications. The proposed antenna is simulated with commercially available packages such as Ansoft HFSS. The antenna gives a moderate gain over operating range while delivering a wide bandwidth.

Polarization signature from the FengYun-3 Microwave Humidity Sounder

Microwave Humidity Sounders (MHS) onboard NOAA-15, -16, -17, -18, -19, and EUMETSAT MetOp-A/B satellites provide radiance measurements at a single polarization state at any of five observed frequencies. The Microwave Humidity Sounder (MWHS) onboard the FengYun-3 (FY-3) satellite has a unique instrument design that provides dual polarization measurements at 150 GHz. In this study, the MWHS polarization signal was investigated using observed and modeled data. It is shown that the quasi-polarization brightness temperatures at 150 GHz display a scan angle dependent bias. Under calm ocean conditions, the polarization difference at 150 GHz becomes non-negligible when the scan angle varies from 10° to 45° and reaches a maximum when the scan angle is about 30°. Also, the polarization state is sensitive to surface parameters such as surface wind speed. Under clear-sky conditions, the differences between horizontal and vertical polarization states at 150 GHz increase with decreasing surface wind speed. Therefore, the polarization signals from the cross-track scanning microwave measurements at window channels contain useful information about surface parameters. In addition, the availability of dual polarization measurements allows a one-to-one conversion from antenna brightness temperature to sensor brightness temperature if a cross-polarization spill-over exists.

The next generation airborne polarimetric Doppler weather radar

Abstract. Results from airborne field deployments emphasized the need to obtain concurrently high temporal and spatial resolution measurements of 3-D winds and microphysics. A phased array radar on an airborne platform using dual-polarization antenna has the potential for retrieving high-resolution, collocated 3-D winds and microphysical measurements. Recently, ground-based phased array radar (PAR) has demonstrated the high time-resolution estimation of accurate Doppler velocity and reflectivity of precipitation and clouds when compared to mechanically scanning radar. PAR uses the electronic scanning (e-scan) to rapidly collect radar measurements. Since an airborne radar has a limited amount of time to collect measurements over a specified sample volume, the e-scan will significantly enhance temporal and spatial resolution of airborne radar observations. At present, airborne weather radars use mechanical scans, and they are not designed for collecting dual-polarization measurements to remotely estimate microphysics. This paper presents a possible configuration of a novel airborne phased array radar (APAR) to be installed on an aircraft for retrieving improved dynamical and microphysical scientific products. The proposed APAR would replace the aging, X-band Electra Doppler radar (ELDORA). The ELDORA X-band radar's penetration into precipitation is limited by attenuation. Since attenuation at C-band is lower than at X-band, the design specification of a C-band airborne phased array radar (APAR) and its measurement accuracies are presented. Preliminary design specifications suggest the proposed APAR will meet or exceed ELDORA's current sensitivity, spatial resolution and Doppler measurement accuracies of ELDORA and it will also acquire dual-polarization measurements.

Characterizing falling snow using multifrequency dual-polarization measurements

Combinations of dual-polarization measurements at various radar frequencies and elevation angles together with realistic scattering computations of snowflakes are compared in order to study how they can be used to characterize falling snow. In the study, we use seven different ice crystal habits, including graupel, and different types of aggregates. The single-particle scattering is modeled using the discrete-dipole approximation, and the backscattering cross sections are integrated over exponential size distributions. We take advantage of statistical properties of the large set of scattering results to determine which combination of measurements provide overall best characterization of snow types. We find that a combination of the differential reflectivity and the depolarization ratios, especially in the circular basis, is useful in the characterization, while the dual-frequency ratios at higher frequencies than the Ku band are almost as good. Also, the assumption of preferential orientation for single ice crystals plays an important role when analyzing the results. These conclusions are tested against both airborne and ground-based radar measurements obtained during the Global Precipitation Measurement Cold-season Precipitation Experiment field campaign in 2012. The results show that dual-polarization and dual-frequency measurements provide complimentary information and can narrow down the characterization of falling snow considerably.