High-latitude & Equatorial Ionospheric Scintillation Based on An Event-Driven Multi-GNSS Data Collection System

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1 High-latitude & Equatorial Ionospheric Scintillation Based on An Event-Driven Multi-GNSS Data Collection System Jade Morton, Yu Jiao, Steve Taylor Electrical and Computer Engineering Department Colorado State University Slide 1

2 Outline 1. Why Event-Driven Multi-GNSS? 1. Sample High-Lat & Equatorial Results Slide 2

3 Amplitude Fading: Receiver Processing Artifacts C/N 0 (db-hz) Tracked C/N 0 Simulated C/N Time(sec) Slide 3

4 GPS Carrier Phase During Deep Fading: An Example Carrier Phase (Cycles) * CTL 10ms FPF 10ms FPF 40ms Signal Intensity (db) Time 2015 (ms) IES Slide 4

5 1. Accuracy 2. Availability Issues: Conventional ISM Receivers (Iono + other) X h(t) = Observed Effects Iono effects Observed Effects 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 High quality, raw GNSS signals are needed for space weather studies and robust GNSS receiver development Slide 5

6 Event Driven Raw Data Collection System Space Weather Events Internet VPN Data Center at Home Institution Commercial ISM Receiver Data Collection and Control Server Space Weather Event Monitoring & Trigger Software Specially designed signal tracking algorithms RF Front End 1 Circular Buffer Scientific analysis RF Front End 2 Circular Buffer Data Storage Algorithm development RF Front End N Circular Buffer Slide 6

7 Event-Driven Multi-Constellation GNSS Network Ethiopia Slide 7

8 Equatorial Scintillation Spatial Distribution Slide 8

9 0.5 Diurnal Patterns Hours after sunset Slide 9

10 Solar Cycle Dependence: High vs. Low Lat Slide 10

11 Percent B Field Variation (nt) Geomagnetic Disturbance Impact on High Latitude H D Z Percent of SV Affected HAARP, AK 7/15/ Time (Hours) Probability of maxσ φ >30 o maxh - minh maxd - mind maxz - minz (H 2 +D 2 +Z 2 ) 1/2 peak-to-peak (nt) σ H σ D σ Z (σ2 +σd 2 +σz 2 ) 1/2 H (nt) Slide 11

12 Frequency Diversity: Selective Fading Slide 12

13 Multi-Frequency Deep Fading Carrier Phaser Reversal During Deep Fading Slide 13

14 Adaptive Joint Time-Frequency Analysis Slide 14

15 Irregularity Dynamics Sensing Using GNSS Array Slide 15

Array Processing: HAARP (Gakona, Alaska) Lat: 62.39 o, Lon: 145.

16 Array Processing: HAARP (Gakona, Alaska) Lat: o, Lon: o W Operation Center Ant 4 3km HF Heating Array Ant 2 North Science Pad 3 Ant 1 1km ¼ km Ant 3 Slide 16

New Alaska Deployment Poker Flat (65.1 o N, 147.

Scatter ISM Receiver Radar (AMISR) OCXO SDR 1 GPS L1/GAL E1 VPN

E5a SDR 3 GAL E5b/BDS B2 SDR 4 GLO L1 Multi-Constellation GNSS

17 New Alaska Deployment Poker Flat (65.1 o N, o W) Poker Flat Advanced Modular Commercial Incoherent Scatter ISM Receiver Radar (AMISR) OCXO SDR 1 GPS L1/GAL E1 VPN Internet Space Weather Event Monitoring & Trigger Software Gakona (62.3 o N, o W) 90% Auroral oval boundary Ant 3 Ant 2 SDR 2 GPS L5/GAL E5a SDR 3 GAL E5b/BDS B2 SDR 4 GLO L1 Multi-Constellation GNSS Receiver Array SDR 5 GLO L2 SDR 6 GPS L2C SDR 7 BDS B1 Data Collection and Control Server Circular Buffer RAID Storage Ant 1 Slide 17

18 Plasma Structure Dynamics Monitoring Slide 18

19 Comparison with SuperDARN Available SuperDARN Data Points vs. σ φ Available SuperDARN Data Points Low/no scintillation Scintillation σ φ (degrees) Slide 19

20 Novel GNSS Receiver Algorithms Adaptive Filtering Adaptive Inter-Channel Frequency Aiding Multi-Constellation Vector Processing Fixed Position Feedback Adaptive Drift Velocity Feedback Slide 20

21 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 21

22 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 2015 Zhang, IES Xin Chen, Hu Wang, Hong Wu, Slide 22 Yanhong Kou.

23 Common Volume LEO and Ground Observations Slide 23

24 Multi-Frequency Fading Analysis Slide 24

25 Fading Overlap: Ascension Island Threshold of detrended signal intensity: -15dB 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 More on Hong Kong, Singapore, and Brazil Very small percentage Slide 25

Equatorial Ionospheric Scintillation

Equatorial Ionospheric Scintillation Based on An Event-Driven GNSS Data Collection System Jade Morton Electrical and Computer Engineering Department Colorado State University USA Slide 1 GNSS Receiver