Making good from bad: Can we use GPS multipath to measure soil moisture? Kristine M. Larson Department of Aerospace Engineering Sciences University of Colorado

2 Outline  GPS basics  Multipath research at CU  If we can’t model multipath, can we extract soil moisture estimates from it?  Preliminary results

3 GPS Basics  Ranges (  from 4 or more satellites are measured.  The position of the GPS antenna and time of the GPS receiver’s clock are estimated.

4 Challenges  We don’t control the GPS satellites.  We can’t directly calibrate the satellites.  We don’t design the receivers we use.  Scientific market share for GPS is <<<< commercial market share.

5 Opportunities  New constellation in Europe (Galileo)  Expanded Russian constellation (Glonass)  Expansion of ground networks and orbiting GPS receivers.

6  Multipath introduces a (frequency dependent) range error  Antenna gain pattern, RHCP/LHCP  for a simple horizontal reflector  multi =2h*(sin  Impacts phase, pseudorange and SNR How does multipath impact gps?

7 Assume reflectance of 10%, L1 frequency

8 Multipath error frequency (for a given receiver/satellite

9 Salar de Uyuni, Boliva  Large salt flat  Sub-decimeter topography; used to calibrate ICESat  Experimental setup:  3 Ashtech Z-12 receivers  2 flush with ground  1 tripod (~1.4m height) Bilich, 2006

10 FIT SNR data Primarily low elevation data

11Results

12 Multipath Assessment: Power Spectral Maps  Idea: frequency and power content of SNR  multipath environment  Method:  Power spectra of small data sections  Assign to satellite azimuth/elevation  Plot all points on a grid

13 MKEA Power Maps 10-30s 30-60s 60-90s s Bilich, 2006

14 Mauna Kea (MKEA)

15 Conclusions I  Multipath frequencies are controlled by obstructions near the antenna.  The ground is the major source of multipath.  Far reflectors are also important, particularly for high-rate applications.  Low elevation data (< 30 degrees) are most corrupted by multipath.  If SNR data accurately map multipath geometries, can they be used to infer multipath reflectivity as well?

16 GPS as a soil moisture instrument  Ratio of reflected to direct GPS signal is proportional to reflectivity.  Reflectivity in turn is proportional to the dielectric constant of the surface.  L-band sensitive to ~ few cm depth.  Wet ground reflects GPS signals better than dry ground. Is it measurable?

17 Why measure Soil moisture?  Important measurement for climate system studies.  Needed for improving models and ground truth for remote sensing studies.  Current instrumentation is sparse (and data are costly to collect). SCAN

18 Past work on GPS reflections Masters, 2004 Reflections from specular locations

19 Limitations  Specialized equipment  Antennas looking down!

20 day of year What does soil moisture look like?

21 Southern California

22 GPS SNR data issues  Negatives  Quality questionable (digitation, L1-L2)  Not much of a published literature.  Positives  No cycle slips  No dependence on orbit quality  Independent for each satellite  Differences with previous reflection work  Use existing GPS instrumentation  No installation costs - but weaker signal.

23 TASH (Tashkent)

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25 What do the SNR data look like?

26 Separate the Arcs

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30 Issues to resolve  Direct signal power  Temperature  Orbital (ground-track)  Vegetation  Comparisons with in situ sensors

31 Known Temperature effects on pseudorange

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33 Katzberg, Torres et al. Vegetation

34 Temperature Effects on Dielectric

35 Soil moisture model  Ethan Gutmann and Eric Small.  Model description: Chen and Dudhia [2001]  Modification of land surface hydrology model MM5 developed by PSU and NCAR.  Make assumptions as to soil type (sand).  We have no in situ radiation data.

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38 Broader Impacts

39 Conclusions  GPS multipath clearly tracks rain events via multipath amplitude changes.  At this time, we cannot explain all the seasonal signal.  We need to work on temperature, power, and vegetation effects.  The “unsolved” GPS error source, multipath, may provide useful information about soil moisture.

40 Acknowledgements  A. Bilich, D. Agnew, P. Axelrad,  IGS, JPL, UNAVCO, NGS, CORS, SOPAC, CDDIS  NASA, CU faculty fellowship.

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