Adaptive Beamspace Processing for Phased-Array Weather Radars

Nai, Feng; Torres, Sebastián; Palmer, Robert D.

doi:10.1109/tgrs.2016.2570138

Cited by 8 publications

(4 citation statements)

References 41 publications

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“…Radar imaging involves transmitting a wide antenna radiation pattern to illuminate a large sector by Barton (1980) and Steyskal (1988) and has been widely used to develop advanced scanning and signal processing techniques for applications including wireless communications (Chryssomallis 2000;Sadhu et al 2017;Roh et al 2014), air surveillance and defense (Van Veen and Buckley 1988;Brookner 2002;Talisa et al 2016), biomedical (Peterson et al 1987), oceanography (McIntosh et al 1995, atmospheric boundary layer (Mead et al 1996) and weather radar observations (Isom et al 2013;Yoshikawa et al 2013;Curtis et al 2016;Nai et al 2016;Kikuchi et al 2017;Mizutani et al 2018;Kurdzo et al 2017;Schvartzman et al 2020).…”

Section: ) Imentioning

confidence: 99%

A Primer on Phased Array Radar Technology for the Atmospheric Sciences

Palmer

Bodine

Kollias

et al. 2022

Bulletin of the American Meteorological Society

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The scientific community has expressed interest in the potential of phased array radars (PARs) to observe the atmosphere with finer spatial and temporal scales. Although convergence has occurred between the meteorological and engineering communities, the need exists to increase access of PAR to meteorologists. Here, we facilitate these interdisciplinary efforts in the field of ground-based PARs for atmospheric studies. We cover high-level technical concepts and terminology for PARs as applied to studies of the atmosphere. A historical perspective is provided as context along with an overview of PAR system architectures, technical challenges, and opportunities. Envisioned scan strategies are summarized because they are distinct from traditional mechanically scanned radars and are the most advantageous for high-resolution studies of the atmosphere. Open access to PAR data is emphasized as a mechanism to educate the future generation of atmospheric scientists. Finally, a vision for the future of operational networks, research facilities, and expansion into complementary radar wavelengths is provided.

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Section: ) Imentioning

confidence: 99%

A Primer on Phased Array Radar Technology for the Atmospheric Sciences

Palmer

Bodine

Kollias

et al. 2022

Bulletin of the American Meteorological Society

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“…Digital beamforming is performed in order to generate beams in elevation. To mitigate ground clutter effects, Capon's method (adaptive beamforming) has been used [49,50], although other ground clutter mitigation methods have also achieved success [51][52][53].…”

Section: Data Collection and Methodsmentioning

confidence: 99%

Observations of a Cold Front at High Spatiotemporal Resolution Using an X-Band Phased Array Imaging Radar

Mahre

Palmer

et al. 2017

Atmosphere

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While the vertical structure of cold fronts has been studied using various methods, previous research has shown that traditional methods of observing meteorological phenomena (such as pencil-beam radars in PPI/volumetric mode) are not well-suited for resolving small-scale cold front phenomena, due to relatively low spatiotemporal resolution. Additionally, non-simultaneous elevation sampling within a vertical cross-section can lead to errors in analysis, as differential vertical advection cannot be distinguished from temporal evolution. In this study, a cold front from 19 September 2015 is analyzed using the Atmospheric Imaging Radar (AIR). The AIR transmits a 20-degree fan beam in elevation, and digital beamforming is used on receive to generate simultaneous receive beams. This mobile, X-band, phased-array radar offers temporal sampling on the order of 1 s (while in RHI mode), range sampling of 30 m (37.5 m native resolution), and continuous, arbitrarily oversampled data in the vertical dimension. Here, 0.5-degree sampling is used in elevation (1-degree native resolution). This study is the first in which a cold front has been studied via imaging radar. The ability of the AIR to obtain simultaneous RHIs at high temporal sampling rates without mechanical steering allows for analysis of features such as Kelvin-Helmholtz instabilities and feeder flow.

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“…Reference [19] discusses the use of adaptive beamspace processing to mitigate this effect. In section V of this paper we analyze a complementary approach for minimizing the impact of the higher near-in sidelobes associated with the use of receive beam clusters.…”

Section: B Sub-array Architecturementioning

confidence: 99%

Command and Control for Multifunction Phased Array Radar

Weber

Cho

Thomas

2017

IEEE Trans. Geosci. Remote Sensing

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Abstract-We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with particular focus on weather surveillance. This command and control (C2) function partitions the available scan time amongst these missions, exploits opportunities to service multiple missions simultaneously and utilizes techniques for increasing scan rate where feasible. After reviewing candidate MPAR architectures and relevant previous research, we describe a specific C2 framework that is consistent with a demonstrated active array architecture using overlapped sub-arrays to realize multiple, concurrent receive beams. Analysis of recently articulated requirements for nearairport and national scale aircraft surveillance indicate that, with this architecture, 40-60% of the MPAR scan timeline would be available for the high-fidelity weather observations currently provided by the Weather Service Radar (WSR-88D) network. We show that appropriate use of sub-array generated concurrent receive beams, in concert with previously documented, complementary techniques to increase the weather scan rate, could enable MPAR to perform full weather volume scans at a rate of 1 per minute. Published observing system simulation experiments, human-in-the-loop studies and radar-data assimilation experiments indicate that 2 high-quality weather radar observations at this rate may significantly improve the lead time and reliability of severe weather warnings relative to current observation capabilities.

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Adaptive Beamspace Processing for Phased-Array Weather Radars

Cited by 8 publications

References 41 publications

A Primer on Phased Array Radar Technology for the Atmospheric Sciences

A Primer on Phased Array Radar Technology for the Atmospheric Sciences

Observations of a Cold Front at High Spatiotemporal Resolution Using an X-Band Phased Array Imaging Radar

Command and Control for Multifunction Phased Array Radar

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