Evaluation of Phased Array Architectures for Weather Observations with Space-Time Processing

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Veröffentlicht in:The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings (2024)
1. Verfasser: Yoon-SL, Kim
Weitere Verfasser: Schvartzman, David, Palmer, Robert D, Tian-You, Yu, Feng Nai, Curtis, Christopher
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The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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024 7 |a 10.1109/RadarConf2458775.2024.10548793  |2 doi 
035 |a 3068177685 
045 2 |b d20240101  |b d20241231 
084 |a 228229  |2 nlm 
100 1 |a Yoon-SL, Kim  |u The University of Oklahoma,Advanced Radar Research Center (ARRC) 
245 1 |a Evaluation of Phased Array Architectures for Weather Observations with Space-Time Processing 
260 |b The Institute of Electrical and Electronics Engineers, Inc. (IEEE)  |c 2024 
513 |a Conference Proceedings 
520 3 |a Conference Title: 2024 IEEE Radar Conference (RadarConf24)Conference Start Date: 2024, May 6 Conference End Date: 2024, May 10 Conference Location: Denver, CO, USAPhased Array Radar (PAR) technology is showing potential to enhance atmospheric observations through its unique capabilities. Among these capabilities, space-time processing is a new way to approach improving weather observation by mitigating clutter in both Doppler and spatial domains through the joint designing of a filter response in both domains. The implementation of space-time processing can take the form of non-adaptive or adaptive space-time weights. Space-time adaptive processing (STAP) can improve clutter mitigation and detection by adaptively adjusting space-time weights. Conversely, non-adaptive space-time processing (STP) has a fixed space-time weights, which leads to sidelobe contamination, limited resolution, and potential inaccuracies in the identification of weather phenomena. This study focuses on the application of STAP and STP to simulated weather data in clutter environment to assess their respective performances. It is worth noting that while STAP offers adaptability, it comes at the cost of increased computational complexity due to its data-dependent nature. To address this challenge, one proposed solution involves the implementation of a subarray architecture within the PAR system. This approach reduces the volume of data to be processed by employing fewer receiving channels while maintaining reasonable data quality. Subsequently, this work explores the trade-offs associated with subarray systems, particularly grating lobes. A potential solution to this issue involves the implementation of an optimized transmit beam pattern. The optimized transmit beam pattern is introduced to reduce the two-way beam patterns especially at the locations of grating lobes, thereby mitigating associated challenges and optimizing system performance. 
653 |a Phased arrays 
653 |a Radar 
653 |a Spacetime 
653 |a Clutter 
653 |a Sidelobes 
653 |a Radar arrays 
653 |a Space-time adaptive processing 
653 |a Meteorological data 
653 |a Adaptability 
653 |a Lobes 
653 |a Environmental 
700 1 |a Schvartzman, David  |u The University of Oklahoma,Advanced Radar Research Center (ARRC) 
700 1 |a Palmer, Robert D  |u The University of Oklahoma,Advanced Radar Research Center (ARRC) 
700 1 |a Tian-You, Yu  |u The University of Oklahoma,Advanced Radar Research Center (ARRC) 
700 1 |a Feng Nai  |u Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma,NOAA/OAR National Severe Storms Laboratory,Norman,OK 
700 1 |a Curtis, Christopher  |u Cooperative Institute for Severe and High-Impact Weather Research and Operations, The University of Oklahoma,NOAA/OAR National Severe Storms Laboratory,Norman,OK 
773 0 |t The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings  |g (2024) 
786 0 |d ProQuest  |t Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3068177685/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch