Quantification of radar QPE performance based on SENSR network design possibilities
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08378551.pdf
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Author(s)
Kurdzo, James M.
Clemons, Emily F.
Cho, John Y. N.
Heinselman, Pamela L.
Yussouf, Nusrat
Date Issued
June 2018
Journal
2018 IEEE Radar Conference (RadarConf18)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kurdzo, James M. et al. “Quantification of Radar QPE Performance Based on SENSR Network Design Possibilities.” 2018 IEEE Radar Conference (RadarConf18), April 2018, Oklahoma City, OK, USA, Institute of Electrical and Electronics Engineers, June 2018 © 2018 IEEE
Version
Author's final manuscript
Abstract
In 2016, the FAA, NOAA, DoD, and DHS initiated a feasibility study for a Spectrum Efficient National Surveillance Radar (SENSR). The goal is to assess approaches for vacating the 1.3- to 1.35-GHz radio frequency band currently allocated to FAA/DoD long-range radars so that this band can be auctioned for commercial use. As part of this goal, the participating agencies have developed preliminary performance requirements that not only assume minimum capabilities based on legacy radars, but also recognize the need for enhancements in future radar networks. The relatively low density of the legacy radar networks, especially the WSR-88D network, had led to the goal of enhancing low-altitude weather coverage. With multiple design metrics and network possibilities still available to the SENSR agencies, the benefits of low-altitude coverage must be assessed quantitatively. This study lays the groundwork for estimating Quantitative Precipitation Estimation (QPE) differences based on network density, array size, and polarimetric bias. These factors create a pareto front of cost-benefit for QPE in a new radar network, and these results will eventually be used to determine appropriate tradeoffs for SENSR requirements. Results of this study are presented in the form of two case examples that quantify errors based on polarimetric bias and elevation, along with a description of eventual application to a national network in upcoming expansion of the work.
MIT Department
Lincoln Laboratory
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/radar.2018.8378551
