Statistical Evaluation of UAS-Based Antenna Measurement for Polarimetric Weather Radars

This article presents advancements in the development and validation of the Radio Frequency Sonde (RFSonde) [1], an unmanned aerial system (UAS) specifically designed for in-situ antenna pattern measurements of fielded weather radar systems. The RFSonde employs a 3-axis gimbal stabilization system, ensuring accurate mechanical polarization alignment of the probe during flights for scanning antenna patterns. The methodology was tested using two operational phased array radar (PAR) systems—Horus [2] and the Advanced Technology Demonstrator (ATD) [3]. A simulation framework was developed to assess critical measurement uncertainties arising from factors such as GNSS positional errors, environmental wind effects, and polarization tracking accuracy. Measured and simulated antenna pattern comparisons allowed us to establish UAS requirements for accurate weather radar calibration. This study also quantified transmit co-polar beam matching biases in differential reflectivity (ΔZ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DR,tx</sub>) and co-polar correlation coefficient (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hv,tx</sub>). Combined with prior work measuring transmitted differential phase (ϕ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DP,tx</sub>) [4], these results demonstrate that the RFSonde can reliably achieve stringent calibration requirements under realistic field conditions. Meeting such calibration standards is essential for accurate weather radar products, such as quantitative precipitation estimation (QPE). Thus, this work validates the RFSonde as a practical, precise, and scalable solution for routine weather radar calibration and validation, potentially enhancing the reliability of radar-based meteorological observations.

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Journal
IEEE Transactions on Radar Systems
Published
2025-01-01
DOI
https://doi.org/10.1109/trs.2025.3588423
Primary Topic
Precipitation Measurement and Analysis
Type
article
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article

Statistical Evaluation of UAS-Based Antenna Measurement for Polarimetric Weather Radars

David Schvartzman, Robert D. Palmer, Antonio R. Segales, Igor R. Ivić et al.
IEEE Transactions on Radar Systems
Precipitation Measurement and Analysis
article

Statistical Evaluation of UAS-Based Antenna Measurement for Polarimetric Weather Radars

David Schvartzman, Robert D. Palmer, Antonio R. Segales, Igor R. Ivić, Khuda Burdi, Noah Zemlin
article en

Abstract

This article presents advancements in the development and validation of the Radio Frequency Sonde (RFSonde) [1], an unmanned aerial system (UAS) specifically designed for in-situ antenna pattern measurements of fielded weather radar systems. The RFSonde employs a 3-axis gimbal stabilization system, ensuring accurate mechanical polarization alignment of the probe during flights for scanning antenna patterns. The methodology was tested using two operational phased array radar (PAR) systems—Horus [2] and the Advanced Technology Demonstrator (ATD) [3]. A simulation framework was developed to assess critical measurement uncertainties arising from factors such as GNSS positional errors, environmental wind effects, and polarization tracking accuracy. Measured and simulated antenna pattern comparisons allowed us to establish UAS requirements for accurate weather radar calibration. This study also quantified transmit co-polar beam matching biases in differential reflectivity (ΔZ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DR,tx</sub>) and co-polar correlation coefficient (ρ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hv,tx</sub>). Combined with prior work measuring transmitted differential phase (ϕ<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DP,tx</sub>) [4], these results demonstrate that the RFSonde can reliably achieve stringent calibration requirements under realistic field conditions. Meeting such calibration standards is essential for accurate weather radar products, such as quantitative precipitation estimation (QPE). Thus, this work validates the RFSonde as a practical, precise, and scalable solution for routine weather radar calibration and validation, potentially enhancing the reliability of radar-based meteorological observations.

IEEE Transactions on Radar SystemsVol. 3
Cooperative Institute for Mesoscale Meteorological Studies (US), NOAA National Severe Storms Laboratory (US), Radar (United States) (US), University of Oklahoma (US)
Climate action
Openalex Percentile: Top 78%
Precipitation Measurement and Analysis
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