A New Algorithm for Phased Array Radar Search Function Improvement in Overload Situations

2011 ◽  
Vol 57 (1) ◽  
pp. 55-63
Author(s):  
Reza Mofrad ◽  
Ramazan Sadeghzadeh
Keyword(s):  
Phased Array ◽  
Simulation Software ◽  
Probability Of Detection ◽  
Beam Forming ◽  
Test Bed ◽  
Simulation Test ◽  
Search Function ◽  
Phased Array Radar ◽  
Maximum Range ◽  
And Performance

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.

scholarly journals Tornado Warning Decisions Using Phased-Array Radar Data

2015 ◽  
Vol 30 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Pamela Heinselman ◽  
Daphne LaDue ◽  
Darrel M. Kingfield ◽  
Robert Hoffman
Keyword(s):  
Lead Time ◽  
Phased Array ◽  
Cognitive Task ◽  
Radar Data ◽  
Probability Of Detection ◽  
Probability Of False Alarm ◽  
Temporal Sampling ◽  
Phased Array Radar ◽  
Tornado Warnings ◽  
Tornado Warning

Abstract The 2012 Phased Array Radar Innovative Sensing Experiment identified how rapidly scanned full-volumetric data captured known mesoscale processes and impacted tornado-warning lead time. Twelve forecasters from nine National Weather Service forecast offices used this rapid-scan phased-array radar (PAR) data to issue tornado warnings on two low-end tornadic and two nontornadic supercell cases. Verification of the tornadic cases revealed that forecasters’ use of PAR data provided a median tornado-warning lead time (TLT) of 20 min. This 20-min TLT exceeded by 6.5 and 9 min, respectively, participants’ forecast office and regions’ median spring season, low-end TLTs (2008–13). Furthermore, polygon-based probability of detection ranged from 0.75 to 1.0 and probability of false alarm for all four cases ranged from 0.0 to 0.5. Similar performance was observed regardless of prior warning experience. Use of a cognitive task analysis method called the recent case walk-through showed that this performance was due to forecasters’ use of rapid volumetric updates. Warning decisions were based upon the intensity, persistence, and important changes in features aloft that are precursors to tornadogenesis. Precursors that triggered forecasters’ decisions to warn occurred within one or two typical Weather Surveillance Radar-1988 Doppler (WSR-88D) scans, indicating PAR’s temporal sampling better matches the time scale at which these precursors evolve.

Research and Realization of Phased Array Radar Functional Simulation System

2014 ◽  
Vol 513-517 ◽  
pp. 2954-2958
Author(s):  
Yu Zhang ◽  
Jun Wang
Keyword(s):  
Phased Array ◽  
System Modeling ◽  
Simulation System ◽  
Simulation Software ◽  
Phased Array Radar ◽  
Target Track ◽  
Functional Simulation ◽  
Coordinate Conversion ◽  
Frame Construction ◽  
Track Simulation

In order to diminish the simulation granularity of phased array radar simulation system, modeling the target track is really necessary. This paper adds the target track simulation module and coordinate conversion module to the original functional simulation system of the phased array radar, thereby presents the frame construction, additional mathematical modules and simulate procedure of the improved simulation system. The phased array radars functional simulation system is proposed for the realization of the actual simulation software system. The simulation result verifies the efficiency of modeling method and mathematical modules.

scholarly journals Impacts of Phased-Array Radar Data on Forecaster Performance during Severe Hail and Wind Events

2015 ◽  
Vol 30 (2) ◽  
pp. 389-404 ◽  
Author(s):  
Katie A. Bowden ◽  
Pamela L. Heinselman ◽  
Darrel M. Kingfield ◽  
Rick P. Thomas
Keyword(s):  
Decision Process ◽  
Phased Array ◽  
Statistical Significance ◽  
Radar Data ◽  
Probability Of Detection ◽  
Control Group ◽  
P Value ◽  
Phased Array Radar ◽  
First Case ◽  
Experimental Group

Abstract The ongoing Phased Array Radar Innovative Sensing Experiment (PARISE) investigates the impacts of higher-temporal-resolution radar data on the warning decision process of NWS forecasters. Twelve NWS forecasters participated in the 2013 PARISE and were assigned to either a control (5-min updates) or an experimental (1-min updates) group. Participants worked two case studies in simulated real time. The first case presented a marginally severe hail event, and the second case presented a severe hail and wind event. While working each event, participants made decisions regarding the detection, identification, and reidentification of severe weather. These three levels compose what has now been termed the compound warning decision process. Decisions were verified with respect to the three levels of the compound warning decision process and the experimental group obtained a lower mean false alarm ratio than the control group throughout both cases. The experimental group also obtained a higher mean probability of detection than the control group throughout the first case and at the detection level in the second case. Statistical significance (p value = 0.0252) was established for the difference in median lead times obtained by the experimental (21.5 min) and control (17.3 min) groups. A confidence-based assessment was used to categorize decisions into four types: doubtful, uninformed, misinformed, and mastery. Although mastery (i.e., confident and correct) decisions formed the largest category in both groups, the experimental group had a larger proportion of mastery decisions, possibly because of their enhanced ability to observe and track individual storm characteristics through the use of 1-min updates.

Optically controlled multiple-beam-forming network for phased-array radar

1998 ◽  
Author(s):  
Yixin Wang ◽  
Shunan Zhong ◽  
Xiaowen Xu ◽  
Shizhi Li ◽  
Liansheng Yin
Keyword(s):  
Phased Array ◽  
Beam Forming ◽  
Multiple Beam ◽  
Phased Array Radar
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