Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment
Date
2019-01-19Author
Zhe, Li
Perera, Sudantha
Zhang, Yan
Zhang, Guifu
Doviak, Richard
Metadata
Show full item recordAbstract
In this paper, a system-specific phased-array radar system simulator was developed, based on a time-domain modeling and simulation method, mainly for system performance evaluation of the future Spectrum-Efficient National Surveillance Radar (SENSR). The goal of the simulation study was to establish a complete data quality prediction method based on specific radar hardware and electronics designs. The distributed weather targets were modeled using a covariance matrix-based method. The data quality analysis was conducted using Next-Generation Radar (NEXRAD) Level-II data as a basis, in which the impact of various pulse compression waveforms and channel electronic instability on weather radar data quality was evaluated. Two typical weather scenarios were employed to assess the simulator’s performance, including a tornado case and a convective precipitation case. Also, modeling of some demonstration systems was evaluated, including a generic weather radar, a planar polarimetric phased-array radar, and a cylindrical polarimetric phased-array radar. Corresponding error statistics were provided to help multifunction phased-array radar (MPAR) designers perform trade-off studies.
Citation
Li, Z.; Perera, S.; Zhang, Y.; Zhang, G.; Doviak, R. Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment. Remote Sens. 2019, 11, 422.
Sponsorship
Funding: The work was supported by NOAA/NSSL through Grant # NA16OAR4320115.A
Open access fees fees for this article provided whole or in part by OU Libraries Open Access Fund.
Acknowledgments: We thank Ramesh Nepal from the Intelligent Aerospace Radar Team (IART) of School of
Electrical and Computer Engineering, the University of Oklahoma as the initial user of the MATLAB Phased-Array
System Toolbox for weather radar simulations at OU, who gave numerous discussions regarding PASIM
implementation. We deeply thank Honglei Chen from MathWorks Inc., who provided important guidance
and support to the weather radar signal statistical modeling and MATLAB tool.
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