1,156 research outputs found

    Prospects of the WSR-88D Radar for Cloud Studies

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    This is the publisher's version, also available electronically from http://journals.ametsoc.org/doi/abs/10.1175/2010JAMC2303.1.Sounding of nonprecipitating clouds with the 10-cm wavelength Weather Surveillance Radar-1988 Doppler (WSR-88D) is discussed. Readily available enhancements to signal processing and volume coverage patterns of the WSR-88D allow observations of a variety of clouds with reflectivities as low as −25 dBZ (at a range of 10 km). The high sensitivity of the WSR-88D, its wide velocity and unambiguous range intervals, and the absence of attenuation allow accurate measurements of the reflectivity factor, Doppler velocity, and spectrum width fields in clouds to ranges of about 50 km. Fields of polarimetric variables in clouds, observed with a research polarimetric WSR-88D, demonstrate an abundance of information and help to resolve Bragg and particulate scatter. The scanning, Doppler, and polarimetric capabilities of the WSR-88D allow real-time, three-dimensional mapping of cloud processes, such as transformations of hydrometeors between liquid and ice phases. The presence of ice particles is revealed by high differential reflectivities and the lack of correlation between reflectivity and differential reflectivity in clouds in contrast to that found for rain. Pockets of high differential reflectivities are frequently observed in clouds; maximal values of differential reflectivity exceed 8 dB, far above the level observed in rain. The establishment of the WSR-88D network consisting of 157 polarimetric radars can be used to collect cloud data at any radar site, making the network a potentially powerful tool for climatic studies

    Radar Detection of High Concentrations of Ice Particles - Methodology and Preliminary Flight Test Results

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    High Ice Water Content (HIWC) has been identified as a primary causal factor in numerous engine events over the past two decades. Previous attempts to develop a remote detection process utilizing modern commercial radars have failed to produce reliable results. This paper discusses the reasons for previous failures and describes a new technique that has shown very encouraging accuracy and range performance without the need for any hardware modifications to industrys current radar designs. The performance of this new process was evaluated during the joint NASA/FAA HIWC RADAR II Flight Campaign in August of 2018. Results from that evaluation are discussed, along with the potential for commercial application, and development of minimum operational performance standards for a future commercial radar product

    Investigation of Advanced Radar Techniques for Atmospheric Hazard Detection with Airborne Weather Radar

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    In 2013 ProSensing Inc. conducted a study to investigate the hazard detection potential of aircraft weather radars with new measurement capabilities, such as multi-frequency, polarimetric and radiometric modes. Various radar designs and features were evaluated for sensitivity, measurement range and for detecting and quantifying atmospheric hazards in wide range of weather conditions. Projected size, weight, power consumption and cost of the various designs were also considered. Various cloud and precipitation conditions were modeled and used to conduct an analytic evaluation of the design options. This report provides an overview of the study and summarizes the conclusions and recommendations

    Doppler Radar for USA Weather Surveillance

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    Polarization techniques for mitigation of low grazing angle sea clutter

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    Maritime surveillance radars are critical in commerce, transportation, navigation, and defense. However, the sea environment is perhaps the most challenging of natural radar backdrops because maritime radars must contend with electromagnetic backscatter from the sea surface, or sea clutter. Sea clutter poses unique challenges in very low grazing angle geometries, where typical statistical assumptions regarding sea clutter backscatter do not hold. As a result, traditional constant false alarm rate (CFAR) detection schemes may yield a large number of false alarms while objects of interest may be challenging to detect. Solutions posed in the literature to date have been either computationally impractical or lacked robustness. This dissertation explores whether fully polarimetric radar offers a means of enhancing detection performance in low grazing angle sea clutter. To this end, MIT Lincoln Laboratory funded an experimental data collection using a fully polarimetric X-band radar assembled largely from commercial off-the-shelf components. The Point de Chene Dataset, collected on the Atlantic coast of Massachusetts’ Cape Ann in October 2015, comprises multiple sea states, bandwidths, and various objects of opportunity. The dataset also comprises three different polarimetric transmit schemes. In addition to discussing the radar, the dataset, and associated post-processing, this dissertation presents a derivation showing that an established multiple input, multiple output radar technique provides a novel means of simultaneous polarimetric scattering matrix measurement. A novel scheme for polarimetric radar calibration using a single active calibration target is also presented. Subsequent research leveraged this dataset to develop Polarimetric Co-location Layering (PCL), a practical algorithm for mitigation of low grazing angle sea clutter, which is the most significant contribution of this dissertation. PCL routinely achieves a significant reduction in the standard CFAR false alarm rate while maintaining detections on objects of interest. Moreover, PCL is elegant: It exploits fundamental characteristics of both sea clutter and object returns to determine which CFAR detections are due to sea clutter. We demonstrate that PCL is robust across a range of bandwidths, pulse repetition frequencies, and object types. Finally, we show that PCL integrates in parallel into the standard radar signal processing chain without incurring a computational time penalty

    CLUTTER DETECTION AND MITIGATION FOR DUAL-POLARIZATION WEATHER RADAR

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    Ground clutter in weather radar observations causes degradation of data quality and can lead to misinterpretation of radar echoes. It is important to detect clutter and mitigate its effects to obtain accurate weather measurements. The focus of this study is to improve the performance of clutter detection algorithms by presenting different discriminant functions. A Bayesian classifier is used to make an optimal decision based on discriminant functions to detect clutter mixed with weather echoes. The conditional probability density functions for clutter and weather signals may change and may need to be updated due to changing weather conditions, clutter, and radar parameters. Therefore, to make it more efficient, a multivariate Gaussian mixture model is presented to parametrize discriminant functions and reduce the complexity of detection algorithms. The model parameters are estimated based on the maximum likelihood, using the Expectation-Maximization (ML-EM) method. A dual-polarization clutter filtering algorithm is also presented to mitigate ground clutter effects on weather radar measurements. A multivariate Gaussian model is introduced to parametrize clutter and weather power spectrums, and the Maximum A Posterior (MAP) method is used to estimate weather components. Instead of using a random phase, the phase of the retrieved weather spectrum is estimated based on the statistical properties of dual-polarization weather signals. The performance of the clutter detection and filtering algorithms are shown by applying them to the radar data collected by the national WSR-88D (KOUN) polarimetric radar and are compared to existing detection and filtering algorithms. It is shown that the proposed algorithms can effectively mitigate clutter effects and substantially improve polarimetric weather radar data quality

    Airborne Doppler radar detection of low altitude windshear

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    As part of an integrated windshear program, the Federal Aviation Administration, jointly with NASA, is sponsoring a research effort to develop airborne sensor technology for the detection of low altitude windshear during aircraft take-off and landing. One sensor being considered is microwave Doppler radar operating at X-band or above. Using a Microburst/Clutter/Radar simulation program, a preliminary feasibility study was conducted to assess the performance of Doppler radars for this application. Preliminary results from this study are presented. Analysis show, that using bin-to-bin Automatic Gain Control (AGC), clutter filtering, limited detection range, and suitable antenna tilt management, windshear from a wet microburst can be accurately detected 10 to 65 seconds (.75 to 5 km) in front of the aircraft. Although a performance improvement can be obtained at higher frequency, the baseline X-band system that was simulated detected the presence of a windshear hazard for the dry microburst. Although this study indicates the feasibility of using an airborne Doppler radar to detect low altitude microburst windshear, further detailed studies, including future flight experiments, will be required to completely characterize the capabilities and limitations

    Cloud radar with hybrid mode towards estimation of shape and orientation of ice crystals

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    This paper is devoted to the experimental quantitative characterization of the shape and orientation distribution of ice particles in clouds. The characterization is based on measured and modeled elevation dependencies of the polarimetric parameters differential reflectivity and correlation coefficient. The polarimetric data are obtained using a newly developed 35 GHz cloud radar MIRA-35 with hybrid polarimetric configuration and scanning capabilities. The full procedure chain of the technical implementation and the realization of the setup of the hybrid-mode cloud radar for the shape determination are presented. This includes the description of phase adjustments in the transmitting paths, the introduction of the general data processing scheme, correction of the data for the differences of amplifications and electrical path lengths in the transmitting and receiving channels, the rotation of the polarization basis by 45°, the correction of antenna effects on polarimetric measurements, the determination of spectral polarimetric variables, and the formulation of a scheme to increase the signal-to-noise ratio. Modeling of the polarimetric variables is based on existing back-scattering models assuming the spheroidal representation of cloud scatterers. The parameters retrieved from the model are polarizability ratio and degree of orientation, which can be assigned to certain particle orientations and shapes. The developed algorithm is applied to a measurement of the hybrid-mode cloud radar taken on 20 October 2014 in Cabauw, the Netherlands, in the framework of the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) campaign. The case study shows the retrieved polarizability ratio and degree of orientation of ice particles for a cloud system of three cloud layers at different heights. Retrieved polarizability ratios are 0.43, 0.85, and 1.5 which correspond to oblate, quasi-spherical, and columnar ice particles, respectively. It is shown that the polarizability ratio is useful for the detection of aggregation/riming processes. The orientation of oblate and prolate particles is estimated to be close to horizontal while quasi-spherical particles were found to be more randomly oriented
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