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Assessing the Weather Observation Capabilities of a Spectrum Efficient National Surveillance Radar Mark E. Weber NOAA OAR National Severe Storms Laboratory 5 December 2017 5 December 2017 1

Transcript of Assessing the Weather Observation Capabilities of a ... · Assessing the Weather Observation...

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Assessing the Weather Observation Capabilities of  a Spectrum Efficient 

National Surveillance RadarMark E. Weber

NOAA OAR National Severe Storms Laboratory5 December 2017

5 December 2017 1

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Fifteen Years of Meteorological Phased Array Radar (PAR) Research

5 December 2017 2

National Weather Radar Testbed

Storm Studies, Scanning Techniques 

and Processing Algorithms

Forecasting Experiments

Technology Risk Reduction

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Multifunction Phased Array Radar (MPAR) Concept

• Multiple stove‐piped radars• Rotating dish technology• Many nearing end‐of‐life

ARSR‐3 ARSR‐4ARSR‐1/2

ASR‐8 ASR‐9 ASR‐11

NEXRAD

Terminal Area

Long Range Aircraft

Long Range Weather

Weather

Current National Operational Radars

FPSMultifunction

Radar

Weather

Aircraft

Ground Based UAS Sense and Avoid

Non-Cooperative Target

Multifunction Phased Array Radar (MPAR)

• Has potential to lower cost by– Reducing number of radar units– Lowering O&M (no moving parts)– Streamlining support infrastructure– Simplifying training and logistics– Open systems procurement and 

maintenance• Enhanced performance

TDWRAircraft

CARSR

5 December 2017 3

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Radio Frequency Spectrum Implications

5 December 2017 4

Air‐Route Surveillance Radar (ARSR): 1.2‐1.4 GHz

Airport Surveillance Radar (ASR): 2.7‐2.9 GHz

Weather Service Radar(WSR‐88D): 2.7‐3.0 GHz

Terminal Doppler Weather Radar (TDWR): 5.5‐5.65 GHz

MPAR: 2.7‐3.0 GHz

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Spectrum Efficient National Surveillance Radar (SENSR)

• “Spectrum Pipeline Plan” proposal– Participating agencies: FAA, NOAA, DoD, DHS– “Phase 1” approved by OMB and NTIA in January 2017

• Feasibility study for release of at least 30 MHz in the 1.30‐1.35 GHz band for non‐federal use– Accomplished by consolidating existing national operational surveillance radar networks

– Consistent with MPAR concept, but alternate approaches (“system‐of‐systems”) under evaluation

• Spectrum Pipeline Act mandates that auction occur by 2024

5 December 2017 5

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SENSR Program Timeline (Unofficial)

5 December 2017 6

.  .   Phase 1  .  .   Feasibility Study

Research and DevelopmentPerformance Requirements 

Concept of OperationsEngineering Analysis

Analysis of AlternativesMarket Survey & RFI

Establish JPO

.   .  .  Phase 2  .  .  .  .  .  .System Maturation 

Industry ContractsDesign / Development

Fly‐off / Vendor Evaluations

.  .  .   Phase 3  .  .  .   

SolutionImplementation 

Limited Production ContractTest / Evaluation

Prep for Spectrum Auction

Spectrum Auction  Mature Requirements

2016 2017 2018 2019 2020 2021 2022 2023 2024

Spectrum Decision andSENSR Solution Implementation Contract Award

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Pending SENSR Architecture Decisions

*Conway et al., 2015 7

Active Array Single Beam

Up/DnConv

TR Modules 

Analog Beamformer

Digital Receiver/Exciter

Analog 

Digital

Digital Subarray

Analog 

Digital

Up/DnConv 

Up/DnConv 

Analog Overlapped Subarray Network

Digital Receiver/Exciter

Digital Beamformer

Beam Cluster

Analog 

Digital

Up/DnConv 

Up/DnConv

Digital Receiver/Exciter

Digital Beamformer

Full Beam Set

All‐Digital 

Up/DnConv

5 December 2017

Antenna Configuration Level of Digitization

Cost*Single‐ or Multi‐Mission Radars

TR Modules 

TR Modules 

A/D A/D

A/D

A/D

A/D A/D

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Preliminary SENSR Performance Requirements

• Five mission areas– Near‐/Short‐/Long‐range aircraft

surveillance (DoD, DHS, FAA)– “Air traffic control” weather (FAA, DoD)– “High resolution” weather (NOAA, FAA, DoD)

• High resolution weather requirements derived from WSR‐88D capabilities– Include goals for one minute volume scan 

updates and flexible, adaptive scanning

• NOAA SENSR feasibility study goals– Assess/refine requirements and provide 

justification– Demonstrate technical approaches to

meeting them

5 December 2017 8

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Outline

• Introduction• NOAA Research Activities• SENSR Program Directions• Summary

95 December 2017

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Framework and Synergies 

Ten Panel Planar Array Demonstrator

Cylindrical Array 

Demonstrator

Advanced Technology 

Demonstrator

PolarimetricCalibration and Correction Technique Evaluation

Computational Electrodynamic 

Modeling

Command and Control 

Analysis and Simulation

Data Quality Analysis and Simulation

Data Assimilation and Warn on 

Forecast Studies

KOUN Rapid Scan Dual‐Pol Data Collection and 

Analysis

Radar NetworkAnalysis and Performance 

Industry Studies 

System Modeling

All‐Digital Array Architecture 

Mission BenefitsCommand and Control andData Quality

Dual Polarization 

Co/Cross Pol Error Models

Scan Strategy RequirementsDwell‐time 

Requirements

Fundamental Research 

29 August 2017 10Hardware Based Evaluation Numerical Simulation Data Analysis

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Warn on Forecast Concept

• Use state‐of‐the‐art high resolution numerical weather prediction (NWP) models to warn public of severe weather threats– 1 km resolution, convection 

resolving– ensembles to characterize 

uncertainty• Continuously assimilate radar 

and satellite data into model 

5 December 2017 11

• Goal is to extend average tornado warning lead times to 40‐60 minutes

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Truth

One

 Minute Scan

s (PAR

)Five M

inute Scan

s (W

SR‐88D

)

Reflectivity (dBZ) Vertical Vel (m/s)

Analysis after 15 minutes of data assimilation

PAR Rapid Volume Scanning Benefit

5 December 2017 Figures from Yussouf and Stensrud, 2010

U (m

/s)

V (m

/s)

W(m

/s)

T (oC)

q (gm/kg)

12

Forecast Time (0‐50 min) 

Forecast Errors for Following 50 Minutes

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Enhanced Low Altitude Coverage Benefit

5 December 2017 Cho, J., “Revised MPAR Network Siting Analysis”, MIT Lincoln Laboratory ATC‐425, 2015 13

All Urban

Aircraft 29 84

Weather 15 49

All Urban

Aircraft 30 89

Weather 30 90

WSR‐88D coverageat 1000’ AGL

Legacy Networks Percent Coverage

MPAR coverageat 1000’ AGL

MPAR Network Percent Coverage

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Planned  Studies

• Warning enhancement benefits for high impact phenomena– Tornadoes, large hail, damaging wind– Flash flooding– Downbursts, convective turbulence, small hail

• Benefits of assimilation of rapid‐scan dual‐polarization observations 

• Sensitivity of benefits to PAR data quality differences

5 December 2017

NSSL Experimental WSR‐88D (KOUN)

Phased Array Radar Testbed

14

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WSR‐88D Volume Coverage Pattern (VCP) 12

5 December 2017 15

Elevation Angle (°)

Number of Tilts

CPI DescriptionMean Scan Time per Tilt (s)

0.5 – 1.3 3

Long PRT scan for range‐unambiguous surveillance

Short PRT scan for Doppler velocity30.8

1.8 – 6.4 6 Interleaved long PRT surveillance and short 

PRT Doppler pulses12.8

8.0 – 19.5 5 Short PRT for Doppler and reflectivity 12.0

24.5 – 60.0 8 Short PRT for Doppler and reflectivity 8.0

Totals 22 293.2

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PAR Rapid Weather Scanning Concepts

1Yu et al. (2007); 2Torres et al. (2013); 3Weber et al. (2017);  4Melnikov et al. (2015) 16

Widened Transmit Beam Multiple Receive Beams 

Tx 1Tx 2

Tx 3

Receive

Beam Multiplexing1Adaptive Weather Scanning2

Receive Beam Clusters3 Multi‐beam Technique4

Time

5 December 2017

Angle1

Angle 2

Time

Angle 3

Angle 4

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Data Quality Simulator

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WWSR

WSR‐88D Base Data(Level II)

Data Conditioning

Spatial Sub‐sampling

Scattering Center 

Simulation

Radar Sampling

WWSR

Simulated Time Series 

Data

Digital Signal Processing

Simulated PAR 

Base Data

PAR Parameters

5 December 2017

• Antenna Patterns• Co/Cross Polar• Transmit/Receive

• Range Sidelobe Patterns• CPI Structure• Single‐Pulse Sensitivity• Range‐Gate Spacing

• Pulse Phase Coding• Simultaneous or Alternate 

H/V Transmit• Antenna Rotation• Volume Coverage Pattern• Split‐Cut Scans

Torres, Boettcher, Curtis, Nai and Schvartzman, IEEE Radar Conference 2018

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Simulation of Angle‐SidelobeImpacts

5 December 2017 Torres, Boettcher, Curtis, Nai and Schvartzman, IEEE Radar Conference 2018 18

Input Data

Simulation‐64 dB min sidelobes

Simulation‐47 dB min sidelobes

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Dual‐Polarization Basics

Polarimetric radar variables are sensitive to hydrometeor (1) size, (2) shape, (3) orientation, (4) density, and (5) water content

Differential reflectivity Zdr = Zh/Zv

Shape

Orientation

Phase composition

Zv Zh 1drZ

1drZ

icewater ( ) ( )water icedr drZ Z

5 December 2017 19

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Phased Array Radar “Geometric Bias” 

5 December 2017 20

Copolar (H)Relative Gain (dB)

Crosspolar (V)Relative Gain (dB)

60o

‐15o

0o

0o‐45o 45o0o‐45o 45o0o

Azimuth Angle (φ)

Elevation An

gle (θ)

ZDR Bias (dB)0

‐10

‐20

‐30

5

0

‐5

Polarization Patterns for Horizontal (H) Dipole Radiating Element

30o

F(φ,θ)  =  Felement(φ,θ)  x  Farray(φ,θ)

‐45o

0

‐5

‐1045o

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Impact of Antenna Architecture

21

Reflector Antenna

• Well‐aligned H/V patterns

• H/V orthogonal at all scan angles

• Cross‐Pol independent of scan angle

Single Face Rotating PAR

• H/V patterns vary with elevation  scan angle

• H/V orthogonal at all elevation scan angles

• Cross‐Pol independent of elevation scan angle

Cylindrical PAR

• H/V patterns vary with elevation  scan angle

• H/V orthogonal at all elevation scan angles

• Cross‐Pol independent of elevation scan angle

Multi‐Face Planar PAR

• H/V patterns vary with az/el  scan angle

• H/V are non‐orthogonal off principal plane

• Cross‐Pol dependent on scan angle

5 December 2017

Increasing Scan Flexibility, Increasing Dual‐Polarization Measurement Challenges

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Calibration, Alignment and Bias Correction Research

• Dual polarization antenna element characterization• Cylindrical array benefits and challenges• In situ calibration and alignment techniques

– Near‐ and far‐field probes– Mutual‐coupling

• Small UAS far‐field calibration probe development• Computational electrodynamic modeling (CEM) correction approaches

• Waveforms and processing techniques that mitigate dual‐pol variable biases

5 December 2017 22

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Polarimetric Calibration Research Infrastructure

23

Far‐Field RangeNear‐Field Range

Dual‐Pol Planar Array Demonstrator (1.6 m2 )

Dual‐Pol Cylindrical Array Demonstrator (1.4 m2) 

Advanced Technology Demonstrator (12.2 m2)

Small UAS Calibration Probe

5 December 2017

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Outline

• Introduction• NOAA Research Activities• SENSR Program Directions• Summary

245 December 2017

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Status

• SENSR Joint‐Agency Program Office (JPO) established

• Industry responses to initial SENSR “Request for Information” have been received and evaluated

• Government review of requirements underway:– Scope– Technical risk– Mission impact

• Expanded interaction with industry planned during “Phase II”

255 December 2017

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Importance

• SENSR likely to be the largest radar procurement in history– Aggregate aperture of radars it will replace is ~15,000 m2

• Offers unique opportunity to modernize national surveillance radar networks using funding from spectrum auction proceeds 

• Significant potential mission benefits for NOAA/NWS– PAR rapid scanning supports enhanced severe weather warning

– SENSR network configuration may improve coverage at low altitude

265 December 2017

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Challenges Imposed by Compressed Acquisition Timeline

• Validating technical requirements appropriate for PAR• Quantifying mission impacts of changes to legacy 

capabilities• Assessing risks in achieving key performance 

parameters (e.g. dual‐polarization variable estimate accuracies)– Can shortfalls be addressed through future planned product improvements?

• Reducing PAR costs well below those of current DoD systems

275 December 2017

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Summary

• Multi‐agency SENSR feasibility study underway

• NOAA’s research program addresses SENSR weather observation requirements, mission benefits and relevant technologies

• Significant NOAA mission benefits possible, but aggressive timeline and evolving multiagency requirements pose challenges 

285 December 2017