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Remote Sensing with Signals of Opportunity
- 2. Garrison, 22 July 2016 Outline • Introduction to Remote Sensing • New methods using GNSS signals • Expansion to “Signals of Opportunity” (SoOp): • S-, Ku and Ka-band Oceanographic sensing • P-band Land remote sensing 2
- 3. Garrison, 22 July 2016 Introduction to Remote Sensing • Working Definition: Remote Sensing: Techniques for inferring properties of the Earth (or another planet’s) land surface, interior, atmosphere, ionosphere or built environment from measurements of electromagnetic (EM) radiation received at a distance. -vs- • In-Situ: (literal: “in the place”) Measurements made in direct contact at the location. Ex. Soil Moisture – Analysis of soil sample – Electromagnetic techniques (“Theta probes”) 3
- 6. Garrison, 22 July 2016 Microwave Remote Sensing • Example measurements from microwave remote sensing: • Ocean wind vectors • Soil moisture • Atmospheric water vapor • Sea surface height • Salinity • Vegetation biomass 6 http://smap.jpl.nasa.gov/mission/
- 7. Garrison, 22 July 2016 Example: Remote Sensing of Soil Moisture 7 Soil Tg Vegetation canopy PT PRα ΓPT TB=εTg Passive Conservation of Energy: Γ=1−ε (for flat surface) Active (Monostatic) PT Prα σ0PT Active (?) (Bistatic)
- 8. Garrison, 22 July 2016 Basic GNSS Navigation 8 cτ1 = (X − X1)2 +(Y −Y1)2 +(Z − Z1)2 +ctb cτ2 = (X − X2 )2 +(Y−Y2 )2 +(Z − Z2 )2 +ctb cτ3 = (X− X3)2 +(Y−Y3)2 +(Z − Z3)2 +ctb cτ4 = (X − X4 )2 +(Y−Y4 )2 +(Z − Z4 )2 +ctb4+ Observations 4 Unknowns τ1 τ2 τ3 τ4 Key to GNSS signal design: Ability to measure delay and Doppler
- 9. Garrison, 22 July 2016 Error Sources: • Variable Propagation speed • Atmospheric bending • Multipath Basic GNSS Navigation τ1 τ2 τ3 τ4 9 One person’s Error is another one’s Signal GNSS signal processing: Reduce the effect of these sources
- 11. Garrison, 22 July 2016 Measurements from Multipath 11 (From Chapron and Ruffini, GNSS-R workshop, Barcelona. Photo taken at Le Conquet, Brittany) This phenomenon can be observed in visible light at sunset: (water is calm inside the red ellipse)
- 13. Garrison, 22 July 2016 Delay-Doppler Ambiguity Monostatic SAR [history.nasa.gov] Bistatic Reflectometry [Zavorotny & Voronovich, 2000] 13
- 19. Garrison, 22 July 2016 Simulated Retrievals 19 Hurricane Danielle (2010): Hurricane Earl (2010):
- 20. Garrison, 22 July 2016 What about other signals ? • Approximately 400 communication satellites in GEO • Fixed incidence angle (GEO) • High-powered (~30 dB above GNSS) signals • Allocations in most bands used for remote sensing: L,S, C, Ku/Ka • Designed for data transmission – Not ranging! • Assumption: Compression & Encryption are very efficient at filling available spectrum – Data is nearly random 20
- 22. Garrison, 22 July 2016 • Hypothesis: Digital satellite communications uses efficient compression and encryption, essentially generating a random signal, enabling delay-Doppler mapping Signals of Opportunity (SoOp) 22 Self-Ambiguity Function [Baker & Griffits, 2005] 8/15/13
- 25. Garrison, 22 July 2016 Platform Harvest Experiment • Data reduction: Coherence Time calculation 25
- 26. Garrison, 22 July 2016 Platform Harvest Experiment • Data reduction: Model Function Development 26
- 27. Garrison, 22 July 2016 • Ku-Band “Code” altimetry Platform Harvest Experiment 27 Parameter Theoretical Experimental SNR [dB] 25.8 25.11 [meters] 0.13 0.13
- 28. Garrison, 22 July 2016 NOAA Hurricane Hunters 28 2014 Hurricane season NOAA P-3 “Hurricane Hunter” aircraft 2-Jul-2014 ~ 17-Sep-2014, 5 hurricanes (Arthur, Bertha, Cristobal, Dolly, and Edouard ) Data processed with Software-Defined Radio
- 30. Garrison, 22 July 2016 NOAA Hurricane Hunters • Software Defined Radio (SDR) processing 30 Cross-correlation Raw Data Curve Fitting Wind Speed Retrieval Filter
- 31. Garrison, 22 July 2016 31 0 500 1000 1500 2000 2500 3000 3500 4000 -5 0 5 10 15 20 25 30 Residue(µs) Waveform No. Delay Residue (Experimental - Theoretical) Residue Theoretical Delay Correlation Waveform NOAA Hurricane Hunters
- 35. Garrison, 22 July 2016 P-band Reflectometry Signals of Opportunity Airborne Demonstrator (SoOp-AD) NASA IIP-13 Selection 35 Parameter SoOp Airborne SoOp Spaceborne Resolution* 100m 870m Antenna Size 75 x 75 cm 75 x 75 cm Sensing Depth 0-30cm 0-30cm Sensing Precision** 0.04m3/m3 0.04m3/m3 *Specular Reflection Assumed **SMAP Requirement
- 36. Garrison, 22 July 2016 • Root Zone Soil Moisture (RZSM): – Water in top ~meter of soil – Critical link between surface hydrology and deeper process – Relatable to drainage and absorption by plant roots – Connection between near-term precipitation and long-term availability of fresh water – No mission currently directly measures RZSM. • Biomass: a related measurement – Carbon storage in vegetation – key part of CO2 balance 36 P-band Reflectometry
- 37. Garrison, 22 July 2016 Comparison to Conventional Methods • L-Band – L-band (SMAP) penetrates only few cm of soil – Saturation at L-band limits the ability to sense soil moisture through vegetation – RZSM from SMAP Level 4 model • P-Band Radar – Difficult to find allocation in heavily utilized spectrum – ESA-BIOMASS cannot operate in North America or Europe due to interference with Space Object Tracking Radar – RFI 37
- 38. Garrison, 22 July 2016 SoOp-AD Solution 38 • We propose to use the principles of reflectometry and reflected SATCOM signals to measure RZSM. – Reutilizing active transmitters with forward scattering presents strong signals even at orbital altitudes. – Specular reflection provides good resolution with small antennas. – Not limited to protected frequency bands and potentially more resilient to RFI. – SoOp-AD will first measure RZSM from an aircraft. – P-Band and S-Band (XM Radio) will be investigated. • SoOp-AD will use geostationary P-Band SATCOM systems – 225-420MHz allocation for government use, SoOp-AD will focus on 240-270MHz band: 18 25KHz channels, 20 5KHz channels. – Continuous use by US since 1978, follow-on systems planning legacy support – SoOp-AD method measures correlation of direct and reflected signals - does not require demod / decode of the transmission. Can work with any noise-like signal source!
- 42. Garrison, 22 July 2016 Antenna System Considerations • Direct-to-Reflect isolation is driving requirement – But not in orbit! • Using “Smart Antenna” to steer a null as necessary in post-processing. • Simulation: Earth View Beam – Co-pol (blue): LHCP – X-pol (red): RHCP • Results simulate a post-processed pattern with a null steered to +40° • Challenge: Calibration of antenna pattern to better than 0.5dB 42 horizon nadir zenith
- 44. Garrison, 22 July 2016 Measurement Simulation • Purpose: – Science requirement flow-down to technology requirements – Error budget – First generation retrieval algorithms • Two Methods: Synthetic (IF) Signal Generator (forward model) and Extended Kalman Filter (inverse estimator) • Evaluate Error Sources against 0.04m3/m3 Precision Req. – SNR – RFI – Direct signal leakage into reflect antenna (easier in orbit!) – Multiple Satellite Interference – Antenna Pattern Knowledge – Aircraft Position & Attitude Knowledge – Number of correlation delays 44
- 45. Garrison, 22 July 2016 Current Model Results 45 -500 -400-300 -200-100 0 100 200 300 400 5000 0.5 1 1.5 2 2.5 3 3.5 4 x 10 -15 Offset (Samples) Correlation 0 Z11 (autocorrelation of channel 1) Z22 (autocorrelation of channel 2) Z12 (cross-correlation between channel 1 and channel 2) Specular delay (τR-τD) Simulated Forward Model Correlation Result
- 46. Garrison, 22 July 2016 Current Modelling Results • Model components: – Thermal noise – Aircraft motion 46
- 47. Garrison, 22 July 2016SoOP-AD - IGARSS 2016 SoOp-AD Tower Campaign 47 Get Jim’s plot • TRL-4 Demonstration • Phase interference with Tower Motion • Data Currently Being Analyzed
- 49. Garrison, 22 July 2016 Conclusions • GNSS signals designed for delay-Doppler mapping was found to have new applications in Earth remote sensing (reflectometry) • New methods for GNSS-Reflectometry (GNSS-R) have been developed - but the field is still very new • Recently, these techniques have been extended to “Signals of Opportunity” • Enable remote sensing measurements in many frequency bands previously “off limits” due to interference • Small, passive receivers, but high SNR measurements • Key to SoOp is a “random” signal - usually achievable as a result of compression and encryption. • New signal processing methods are needed to extract scientifically useful observations - drawing from work in both the navigation and microwave remote sensing fields 49