KOSPAW Test bed—A Phased Array Radar for Space Situational Awareness

Author(s):  
Jiwoong Yu ◽  
Sungki Cho ◽  
Jung Hyun Jo
Author(s):  
Jonghyun Lee ◽  
Eun Jung Choi ◽  
Hyun-Wook Moon ◽  
Joontae Park ◽  
Sungki Cho ◽  
...  

2016 ◽  
Vol 31 (1) ◽  
pp. 43-55 ◽  
Author(s):  
Katie A. Bowden ◽  
Pamela L. Heinselman

Abstract The 2013 Phased Array Radar Innovative Sensing Experiment (PARISE) investigated the impacts of higher-temporal-resolution radar data on National Weather Service forecasters’ warning decision processes during severe hail and wind events. In total, 12 forecasters participated in the 2013 PARISE over a 6-week period during the summer of 2013. Participants were assigned to either a control [5-min phased-array radar (PAR) updates] or experimental (1-min PAR updates) group, and worked two cases in simulated real time. This paper focuses on the qualitative retrospective reports of participants’ warning decision processes that were collected using the recent case walk-through method. Timelines of participants’ warning decision process were created for both cases, which were then thematically coded according to a situational awareness framework. Coded themes included perception, comprehension, and projection. It was found that the experimental group perceived significantly more information during both cases than the control group (case 1 p = 0.045 and case 2 p = 0.041), which may have improved the quality of their comprehensions and projections. Analysis of timelines reveals that 1-min PAR updates were important to the experimental group’s more timely and accurate warning decisions. Not only did the 1-min PAR updates enable experimental participants to perceive precursor signatures earlier than control participants, but through monitoring trends in radar data, the experimental group was able to better detect storm motion, more accurately identify expected weather threats from severe thunderstorms, more easily observe strengthening and diminishing trends in storms, and make more correct tornado-related warning decisions.


2011 ◽  
Vol 57 (1) ◽  
pp. 55-63
Author(s):  
Reza Mofrad ◽  
Ramazan Sadeghzadeh

A New Algorithm for Phased Array Radar Search Function Improvement in Overload SituationsA new algorithm is proposed for phased array radar search function resource allocation. The proposed algorithm adaptively priorities radar search regions and in overload situations, based on available resources, radar characteristics, maximum range and search regions, optimally allocates radar resources in order to maximize probability of detection. The performance of new algorithm is evaluated by the multifunction phased array radar simulation test bed. This simulation test bed provides capability to design and evaluate the performance of different radar resource management, target tracking and beam forming algorithms. Some results are presented that show capabilities of this simulation software for multifunction radar algorithms design and performance evaluation.


2015 ◽  
Vol 30 (4) ◽  
pp. 933-956 ◽  
Author(s):  
Charles M. Kuster ◽  
Pamela L. Heinselman ◽  
Marcus Austin

Abstract On 31 May 2013, a supercell produced a tornado rated as 3 on the enhanced Fujita scale (EF3) near El Reno, Oklahoma, which was sampled by the S-band phased-array radar (PAR) at the National Weather Radar Testbed in Norman, Oklahoma. Collaboration with the forecaster who issued tornado warnings for the El Reno supercell during real-time operations focused the analysis on critical radar signatures frequently assessed during warning operations. The wealth of real-world experience provided by the forecaster, along with the quantitative analysis, highlighted differences between rapid-scan PAR data and the Weather Surveillance Radar-1988 Doppler located near Oklahoma City, Oklahoma (KTLX), within the context of forecast challenges faced on 31 May 2013. The comparison revealed that the 70-s PAR data proved most advantageous to the forecaster’s situational awareness in instances of rapid storm organization, sudden mesocyclone intensification, and abrupt, short-term changes in tornado motion. Situations where PAR data were most advantageous in the depiction of storm-scale processes included 1) rapid variations in mesocyclone intensity and associated changes in inflow magnitude; 2) imminent radar-indicated development of the short-lived (EF0) Calumet, Oklahoma, and long-lived (EF3) El Reno tornadoes; and 3) precise location and motion of the tornado circulation. As a result, it is surmised that rapid-scan volumetric radar data in cases like this would augment a forecaster’s ability to observe rapidly evolving storm features and deliver timely, life-saving information to the general public.


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