Using GPS to measure ground complex permittivity

Kavak, Adnan; Vogel, W.J.; Xu, Guanghan

doi:10.1049/el:19980180

Cited by 58 publications

(22 citation statements)

References 3 publications

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“…There is a type of GPS-R that relies on the multipath reception of simultaneously and coherently recorded directly and reflected signals. It employs signal-to-noise ratio (SNR) measurements for retrieving environmental parameters such as soil moisture (Kavak et al, 1998;Larson et al, 2008;RodriguezAlvarez et al, 2011;Chew et al, 2014;Alonso-Arroyo et al, 2014), snow depth (Jacobson, 2008;Larson et al, 2009;Rodriguez-Alvarez et al, 2012;Nievinski and Larson, 2014d;Jin and Najibi, 2014), vegetation growth Rodriguez-Alvarez et al, 2011;Wan et al, 2014), and sea level variations (Anderson, 2000;Lö fgren et al, 2014). The technique samples the environment over a sizable area, e.g., $1000 m 2 in the vicinity of a 2-m tall GPS antenna.…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers have used a custom designed GPS antenna coupled with a commercial off-the-shelf (COTS) receiver to record multipath signals (Rodriguez-Alvarez et al, 2011); others have employed a completely COTS antenna/receiver system in a setup dedicated for environmental monitoring, normally deployed tipped towards the horizon, sometimes upside-down (Kavak et al, 1998;Anderson, 2000;Jacobson, 2008;Lö fgren et al, 2014). In contrast, Larson et al (2008) first demonstrated that SNR measurements from COTS equipment and upright setups in existing GPS sites -deployed for positioning purposes -are in a good agreement with nearby precipitation records and land surface model predictions for soil moisture fluctuations.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

Tabibi

Geremia‐Nievinski

Dam

et al. 2015

Advances in Space Research

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Global Positioning System (GPS) signal-to-noise ratio (SNR) measurements can be employed to retrieve environmental variables in multipath reception conditions, whereby direct or line-of-sight transmission is received simultaneously with coherent reflections thereof. Previous GPS SNR multipath studies of soil moisture and snow depth have focused on the legacy GPS L1 and L2 bands. In the present paper, short-delay, near-grazing incidence multipath from the L5-band GPS SNR is assessed for its value in detecting soil moisture and snow depth. The L5 signal will become more important in the future because of compatibility and interoperability among the different global satellite navigation systems. The L5 results are compared with L2C estimates to determine whether the L2C-L5 differences (given their differing power budgets and their modulation properties) are significant. To address these questions, measurements and simulations were employed. A physically-based multipath simulator was enhanced to investigate the differences between parameter retrievals for the L2C and the L5 GPS signals. Parameter retrievals from synthetic observations for different scenarios were compared. Comparisons included varying reflector height, surface material, and surface roughness. Measurements from two GPS stations in Colorado, USA, were used to retrieve soil moisture and snow depth conditions. Over a 153-day period that encompassed the catastrophic 2013 Colorado flooding event, L2-derived volumetric soil moisture had an RMS difference of 0.042 cm 3 /cm 3 while the L5 RMS difference was 0.034 cm 3 / cm 3 with respect to in-situ data (values of volumetric soil moisture range between 0.04 and 0.34 cm 3 /cm 3 ). In a separate 483-day campaign, L5-derived snow depth estimates were compared to L2C-derived values and found strongly correlated, deviating from a one-toone relationship by only 0.00001 ± 0.0064 cm/cm. These results indicate the absence of any detectable biases in L5 as compared to L2C for retrieving soil moisture and snow depth from GPS SNR multipath observations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

Tabibi

Geremia‐Nievinski

Dam

et al. 2015

Advances in Space Research

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“…Recently, it has been reported that reflected GPS signals can provide useful information about the land-surface composition such as snow depth, lake ice thickness, soil moisture, ground electrical characteristics, or sea ice conditions [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. The possibility of estimating dry snow density with the GPS L1 frequency was first mentioned by Jacobson [5].…”

Section: Introductionmentioning

confidence: 99%

Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals

Jacobson

2010

Remote Sensing

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A nonlinear least squares fitting algorithm is used to estimate both snow depth and snow density for a snow-layer above a flat ground reflector. The product of these two quantities, snow depth and density, provides an estimate of the snow water equivalent. The input to this algorithm is a simple ray model that includes a speculary reflected signal along with a direct signal. These signals are transmitted from the global positioning system satellites at 1.57542 GHz with right-hand circularly polarization. The elevation angles of interest at the GPS receiving antenna are between 5° and 30°. The results from this nonlinear algorithm show potential for inferring snow water equivalent using GPS multipath signals.

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“…In a scatterometric approach, GPS reflections have been used to infer sea roughness parameters and thus wind speeds [9]. Ionospheric sensing [10], soil moisture measurements [11], and sea ice observations [12] are some other applications under investigation. Growing experience from space experiments is expected for the coming years.…”

Section: Introductionmentioning

confidence: 99%

Potential of Reflected GNSS Signals for Ice Sheet Remote Sensing

Wiehl¹,

Legrésy²,

Dietrich³

2003

PIER

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Abstract-Earth-reflected GNSS (Global Navigation Satellite System) signals have become an attractive tool for remote sensing, e.g., ocean altimetry and scatterometric ocean wind measurements. For ice sheets, the large penetration capability and the large-scale surface averaging of the L-band signals could open a new look on firnpack characteristics like accumulation rates. In this paper we investigate theoretically reflections of GPS (Global Positioning System) signals from ice sheets. We derive a model of the reflection signal and perform simulations of airborne and spaceborne measurements. The results show that the signal, though complex, is sensitive to the roughness of the snow surface (and internal interfaces) and to firn parameters like accumulation rates. To extract valuable and concise information from the complex signal, we derive an example procedure that focusses on particular ground zones during a satellite receiver pass. The results indicate that it should be possible in principle to separately infer surface and firnpack parameters from the measurements. We conclude that GNSS reflections over ice sheets should be further persued, in particular by obtaining experimental data.

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Using GPS to measure ground complex permittivity

Cited by 58 publications

References 3 publications

Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

Inferring Snow Water Equivalent for a Snow-Covered Ground Reflector Using GPS Multipath Signals

Potential of Reflected GNSS Signals for Ice Sheet Remote Sensing

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