Slide 1 2015 IES

Jade Morton, Yu Jiao, Steve Taylor Electrical and Computer Engineering Department

Colorado State University

High-latitude & Equatorial Ionospheric Scintillation Based on

An Event-Driven Multi-GNSS Data Collection System

Slide 2 2015 IES

Outline

1. Why Event-Driven Multi-GNSS ? 1. Sample High-Lat & Equatorial Results

Slide 3 2015 IES

Amplitude Fading: Receiver Processing Artifacts

50 52 54 56 58 600

5

10

15

20

25

30

35

40

45

Time(sec)

C/N 0(d

B-Hz

)

Tracked C/N0

Simulated C/N0

Slide 4 2015 IES

GPS Carrier Phase During Deep Fading: An Example

-1.5

-1

-0.5

0

0.5

-40

-30

-20

-10

Time (ms)

Sign

al In

tens

ity

(dB

) C

arrie

r Pha

se

(Cyc

les)

20 40 60 80

-10 -20 -30 -40

0.5

0

0.5

1

1.5

CTL 10ms FPF 10ms FPF 40ms *

Slide 5 2015 IES

Issues: Conventional ISM Receivers

High quality, raw GNSS signals are needed for space weather studies and

robust GNSS receiver development

1. Accuracy (Iono + other) X h(t) = Observed Effects

Iono effects ≠ Observed Effects

2. Availability Receivers cease to function during strong space weather events Data are not available when needed most!

3. Repeatability Receiver processing is irreversible Ionosphere effects are wiped out during processing

Slide 6 2015 IES

Event Driven Raw Data Collection System

Commercial ISM Receiver

RF Front End 1

RF Front End 2

RF Front End N

Space Weather Events

Data Collection and Control Server

Space Weather Event Monitoring & Trigger

Software

Circular Buffer

Circular Buffer

Circular Buffer

Dat

aS

tora

ge

VPN

Data Center at Home Institution

Inte

rnet

Specially designed signal tracking algorithms

Scientific analysis Algorithm development

Slide 7 2015 IES

Event-Driven Multi-Constellation GNSS Network

Ethiopia

Slide 8 2015 IES

Equatorial Scintillation Spatial Distribution

Slide 9 2015 IES

Diurnal Patterns

0 6 12 18 240

0.1

0.2

0.3

0.4

0.5

Hours after sunset

Slide 10 2015 IES

Solar Cycle Dependence: High vs. Low Lat

Slide 11 2015 IES

0

100

-800

0

800

P

erce

nt

B F

ield

Var

iatio

n (n

T)

H

D

Z

Percent of SV Affected

Geomagnetic Disturbance Impact on High Latitude

0 2 4 6 8 10 12 14 16 18 20 22 24Time (Hours)

HAARP, AK 7/15/2012

0 500 1000 1500 2000

0.4

0.6

0.8

1

(nT)

Prob

abili

ty o

f maxσ φ

>30o

maxH - minHmaxD - minDmaxZ - minZ

(H2+D2+Z2)1/2peak-to-peak

0 150 300 450

0.4

0.6

0.8

1

(nT)

σH

σD

σZ

(σH2+σ

D2+σ

Z2)1/2

Slide 12 2015 IES

Frequency Diversity: Selective Fading

Slide 13 2015 IES

Multi-Frequency Deep Fading

Carrier Phaser Reversal During Deep Fading

Slide 14 2015 IES

Adaptive Joint Time-Frequency Analysis

Slide 15 2015 IES

Irregularity Dynamics Sensing Using GNSS Array

Slide 16 2015 IES

Array Processing: HAARP (Gakona, Alaska) Lat: 62.39o, Lon: 145.15oW

NorthHF Heating Array

Operation Center

Ant 1

Ant 2

Ant 3Science Pad 3

Ant 4

1km

3km

¼ km

Slide 17 2015 IES

Commercial ISM Receiver

SDR 1GPS L1/GAL E1

SDR 3GAL E5b/BDS B2

Data Collection and Control Server

Space Weather Event Monitoring & Trigger

Software

VPN

Internet

SDR 6GPS L2C

SDR 7BDS B1

SDR 2GPS L5/GAL E5a

SDR 4GLO L1

SDR 5GLO L2

Circular Buffer

RAID Storage

OCXO

Gakona

Poker Flat(65.1oN, 147.5oW)

(62.3oN, 145.3oW)

90% Auroral oval boundary

New Alaska Deployment Poker Flat Advanced Modular Incoherent Scatter Radar (AMISR)

Multi-Constellation GNSS Receiver Array

Ant 1

Ant 2

Ant 3

Slide 18 2015 IES

Plasma Structure Dynamics Monitoring

Slide 19 2015 IES

0 5 10 15 20 25 30 35 40 450

250

500

750

1000

1250

1500

1750

σφ (degrees)

Ava

ilabl

e S

uper

DA

RN

Dat

a P

oint

sAvailable SuperDARN Data Points vs. σ

φ

Scintillation

Low/no scintillation

Comparison with SuperDARN

Slide 20 2015 IES

Novel GNSS Receiver Algorithms

• Adaptive Filtering

• Adaptive Inter-Channel Frequency Aiding

• Multi-Constellation Vector Processing

• Fixed Position Feedback

• Adaptive Drift Velocity Feedback

Slide 21 2015 IES

Conclusions

• High quality GNSS data is needed for – Continuous, accurate interpretation of ionosphere processes – Robust GNSS receivers development

• Successful data collection system yielding both known results as well as new observations – Adaptive processing is needed – Computation cost need to be improved

Slide 22 2015 IES

Acknowledgements

• Funding support from: – AFOSR, AFRL, NSF, DAGSI, Miami Univ., Colorado State Univ. – Industrial support: Rockwell Collins, Honeywell, Northrop Grumman, Mitre

Co., Lockheed Martin, Topcon, Symmetricom, Septentrio, Novatel, John Deere. • Collaborators:

– Ohio University, AFIT, University of Alaska Fairbanks, Singapore Nanyang Technical University, Hong Kong Polytechnic University, Boston College, Stanford University, University of Colorado Boulder, University of Hawaii

– Arecibo Observatory, Jicamarca Radio Observatory, Poker Flat Rocket Range and HAARP, Sondrestrom Observatory.

• Students/Post-docs: – Harrison Bourne, Steve Taylor, Jun Wang, Joy Jiao, Dongyang Xu, Brian

Breitsch, Jack Hall, Brian Jamieson, Mark Carroll, Robert Cole, Hang Yin, Richard Marcus, Mellissa Simms, Fan Zhang, Kyle Wyan, Kyle Kauffman, Xiaolei Mao, Ruihui Di, Fei Niu, Ryan Wolfarth, Praveen Vikram, Dan Charney, Greg Distler, Greg Newstadt, Adam Hill, Matt Cosgrove, Nick Matteo, Aaron Pittenger, Priyanka Chandrasekaran, Cheng Wang, Xiaoli Liu, Senlin Peng, Nazalie Kassanbian, Lei Zhang, Xin Chen, Hu Wang, Hong Wu, Yanhong Kou.

Slide 23 2015 IES

Common Volume LEO and Ground Observations

Slide 24 2015 IES

Multi-Frequency Fading Analysis

Slide 25 2015 IES

Fading Overlap: Ascension Island

Very small percentage

Fading band L1 L2C L5

L1 only 95.3% / /

L2C only / 82.9% /

L5 only / / 80.7%

Concurrent L1 and L2C 3.0% 1.3% /

Concurrent L1 and L5 1.4% / 0.7%

Concurrent L2C and L5 / 15.7% 18.5%

Concurrent L1, L2C and L5 0.2% 0.1% 0.1%

Fading Number

L1 1,791

L2C 4,591

L5 1,584

Total 7,966

Threshold of detrended signal intensity: -15dB

Concurrent L1, L2C and L5 0.2% 0.1% 0.1%

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