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 2015 IES Slide 1
Outline 1. Why Event-Driven Multi-GNSS ? 1. Sample High-Lat & Equatorial Results 2015 IES Slide 2
Amplitude Fading: Receiver Processing Artifacts 45 40 35 30 C/N 0 (dB-Hz) 25 20 15 Tracked C/N 0 10 Simulated C/N 0 5 0 50 52 54 56 58 60 Time(sec) 2015 IES Slide 3
GPS Carrier Phase During Deep Fading: An Example 0.5 0.5 Carrier Phase (Cycles) 0 0 CTL 10ms 0.5 -0.5 FPF 10ms 1 -1 * FPF 40ms 1.5 -1.5 -10 -10 Signal Intensity -20 -20 (dB) -30 -30 -40 -40 20 40 60 80 Time (ms) 2015 IES Slide 4
Issues: Conventional ISM Receivers 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 High quality, raw GNSS signals are needed for space weather studies and robust GNSS receiver development 2015 IES Slide 5
Event Driven Raw Data Collection System Data Center at Home Institution Internet Space Weather Events VPN Data Collection and Control Specially designed Server signal tracking Space Weather Event algorithms Commercial ISM Monitoring & Trigger Receiver Software Scientific Circular Buffer RF Front End 1 analysis Storage Data Circular Buffer Algorithm RF Front End 2 development RF Front End N Circular Buffer 2015 IES Slide 6
Event-Driven Multi-Constellation GNSS Network Ethiopia 2015 IES Slide 7
Equatorial Scintillation Spatial Distribution 2015 IES Slide 8
Diurnal Patterns 0.5 0.4 0.3 0.2 0.1 0 0 6 12 18 24 Hours after sunset 2015 IES Slide 9
Solar Cycle Dependence: High vs. Low Lat 2015 IES Slide 10
Geomagnetic Disturbance Impact on High Latitude 800 Percent B Field Variation (nT) HAARP, AK 7/15/2012 H D 0 Z -800 100 Percent of SV Affected 0 0 2 4 6 8 10 12 14 16 18 20 22 24 Time (Hours) 1 1 Probability of max σ φ >30 o 0.8 0.8 σ H maxH - minH 0.6 0.6 σ D maxD - minD σ Z maxZ - minZ (H2+D2+Z2)1/2 0.4 0.4 ( σ H 2+ σ D 2+ σ Z 2)1/2 peak-to-peak 2015 IES 0 500 1000 1500 2000 0 150 300 450 Slide 11 (nT) (nT)
Frequency Diversity: Selective Fading 2015 IES Slide 12
Multi-Frequency Deep Fading Carrier Phaser Reversal During Deep Fading 2015 IES Slide 13
Adaptive Joint Time-Frequency Analysis 2015 IES Slide 14
Irregularity Dynamics Sensing Using GNSS Array 2015 IES Slide 15
Array Processing: HAARP (Gakona, Alaska) Lat: 62.39 o , Lon: 145.15 o W Ant 4 Operation Center 3km North HF Heating Array Ant 2 1km Ant 1 Ant 3 ¼ km Science Pad 3 2015 IES Slide 16
New Alaska Deployment Poker Flat Poker Flat (65.1 o N, 147.5 o W) Internet Advanced Modular Commercial VPN Incoherent Scatter Radar ISM Receiver (AMISR) OCXO Space Weather Event Monitoring & Trigger SDR 1 Software GPS L1/GAL E1 SDR 2 Data Collection and GPS L5/GAL E5a Control Server Ant 3 SDR 3 GAL E5b/BDS B2 Gakona SDR 4 Circular (62.3 o N, 145.3 o W) GLO L1 Buffer Multi-Constellation SDR 5 GNSS Receiver GLO L2 Ant 1 Array SDR 6 GPS L2C 9 0 % SDR 7 RAID Storage A u r o r a BDS B1 l o v a Ant 2 l b o u n d a r y 2015 IES Slide 17
Plasma Structure Dynamics Monitoring 2015 IES Slide 18
Available SuperDARN Data Points vs. σ φ Comparison with SuperDARN 1750 Low/no scintillation 1500 Available SuperDARN Data Points Scintillation 1250 1000 750 500 250 0 0 5 10 15 20 25 30 35 40 45 σ φ (degrees) 2015 IES Slide 19
Novel GNSS Receiver Algorithms • Adaptive Filtering • Adaptive Inter-Channel Frequency Aiding • Multi-Constellation Vector Processing • Fixed Position Feedback • Adaptive Drift Velocity Feedback 2015 IES Slide 20
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 2015 IES Slide 21
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, 2015 IES Slide 22 Yanhong Kou.
Common Volume LEO and Ground Observations 2015 IES Slide 23
Multi-Frequency Fading Analysis 2015 IES Slide 24
Fading Overlap: Ascension Island Threshold of detrended signal intensity: -15dB Fading band L1 L2C L5 Fading Number L1 only 95.3% / / L1 1,791 L2C only / 82.9% / L2C 4,591 L5 1,584 L5 only / / 80.7% Total 7,966 Concurrent 3.0% 1.3% / L1 and L2C Concurrent More on Hong Kong, 1.4% / 0.7% L1 and L5 Singapore, and Brazil Concurrent / 15.7% 18.5% L2C and L5 Concurrent Concurrent Very small percentage 0.2% 0.1% 0.1% 0.2% 0.1% 0.1% L1, L2C and L5 L1, L2C and L5 2015 IES Slide 25
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