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Spaceborne radar sounders are high frequency (HF)/very high frequency (VHF) nadir-looking sensors devoted to subsurface investigations. Their data interpretation can be severely hindered by off-nadir surface clutter. Recent literature showed that the clutter suppression capabilities of this class of systems can be greatly enhanced by deploying an array of orbiting sensors in formation flight synthesizing a narrow radar antenna beam. In this article, we assess the capability of distributed radar sounding to discriminate clutter from subsurface returns by exploiting direction of arrival (DOA) estimation techniques. This is achieved by first outlining an approach for designing and evaluating the distributed radar sounder DOA estimation performance as function of the radar system parameters (e.g., intersensor distance) and external noise factors such as ionospheric scintillations. Then, the theory is complemented by radar simulations of several acquisitions over Greenland assuming a variety of subsurface geometries. The simulations confirm that clutter discrimination through DOA estimation is a viable approach to further improve the array capability in disambiguation of subsurface echoes from surface ones. [ABSTRACT FROM AUTHOR]

An intrinsic challenge in the geophysical interpretation of low-frequency synthetic aperture radar (SAR) imagery of semitransparent media, such as ice sheets, is the position ambiguity of the scattering structures within the glacial volume. Commonly tackled by applying interferometric and tomographic techniques, their spaceborne implementation exhibits by orders higher complexity compared to missions relying on single SAR images, making them cost expensive or, in the context of planetary missions, even impossible due to limited navigation capability. Besides, even these sophisticated techniques are commonly biased due to inaccurate permittivity estimates, leading to geometric distortions up to several meters. We present a novel inversion procedure to estimate volume parameters of ice sheets, namely, the depth of the scattering layer within the glacial volume and the dielectric permittivity of the ice, based on single-image single-polarization SAR acquisitions. The information is inherent in the processed SAR data as phase errors on the azimuth signals resulting from uncompensated nonlinear propagation of the radar echoes through ice. We suggest a local map-drift autofocus approach to quantify and spatially resolve the phase errors and an inversion model to relate them to the penetration depth and permittivity. Testing the proposed technique using P-band SAR data acquired using DLR’s airborne sensor F-SAR during the ARCTIC15 campaign in Greenland shows promising results and good agreement with tomographic products of the analyzed test site. [ABSTRACT FROM AUTHOR]

Accurate measurements of fast flowing outlet glaciers in Greenland and Antarctica are of vital importance to improve ice-sheet models that predict the ice-sheets’ contribution to sea-level rise over the next century. Radars with high sensitivity and advanced processing capabilities are required to sound ice in fast-flowing glaciers. We developed the multichannel coherent radar depth sounder/imager (MCoRDS/I) for ice thickness measurements and 3-D imaging of bedrock over important areas of Greenland and Antarctica. Radio frequency interference (RFI) degrades the sensitivity of the MCoRDS/I system, thus affecting the quality of the data collected. Data from the 2010 Greenland field season exhibited a degraded signal-to-noise ratio (SNR), requiring extensive RFI analysis, investigation, and mitigation for the MCoRDS/I system. Measurements were taken in an electromagnetic interference (EMI) chamber on individual sections of the MCoRDS/I system to isolate the sources of RFI. Then, RFI mitigation techniques were implemented for the offending sections and EMI chamber measurements verified the integrity of the solution prior to the 2011 Greenland deployment. Recorded data from the 2011 Greenland field season also verified that the RFI mitigation resulted in more than 20 dB improvement in the SNR compared to the 2010 Greenland data. The reduction of EMI emissions has also been beneficial to data collection in subsequent deployments. [ABSTRACT FROM AUTHOR]

This paper focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume, and how they may contribute to global climate change. The time-consuming manual approach requires sparse hand-selection of surface and bedrock interfaces by several human experts, and interpolating between the selections to save time. Two primary methods have been studied in this paper, namely, edge-based and active contour. Results are evaluated and presented using the metrics of time requirements and accuracy. Automated ice thickness estimation results from 2006 and 2007 Greenland field campaigns illustrate that the edge-based approach offers faster processing (seconds compared to minutes), but suffers from a lack of continuity and smoothness aspects that active contours provide. The active contour approach is more accurate when compared to ground truth selections provided by human experts, and has proven to be more robust to image artifacts. It is shown that both techniques offer advantages which could be integrated to yield a more effective system. [ABSTRACT FROM AUTHOR]

An extended Kalman filter (EKF) to estimate the ionospheric total electron content (TEC) along the radar line-of-sight has been developed. By varying the carrier frequency of consecutive radar pulses, it is shown that the TEC along the line-of-sight becomes observable and can be estimated in real-time to a high degree of accuracy. It is shown that the filtering formulation presented here optimally reduces the randomly varying range bias caused by the irregular electron density structure in the upper atmosphere. The performance of the tracking filter is examined with a Monte Carlo simulation analysis. It is shown that for a radar located in Thule, Greenland and operating at a nominal frequency of 435 MHz (UHF), an improvement of approximately 50% in the range estimation accuracy is achieved with a frequency separation of 18 MHz between two consecutive pulses. if the frequency separation is increased to 60 MHz, the increase in accuracy is 75%. It is also shown that in the absence of frequency separation, the performance of the tracking filter presented here reduces to that of a conventional six-state EKF that does not account for the ionospheric bias. [ABSTRACT FROM AUTHOR]

Snow accumulation in remote regions, such as Green- land and Antarctica, is a key factor for estimating the Earth's ice mass balance. In situ data are sparse; hence, they are useful to derive snow accumulation from remote sensing observations, such as microwave thermal emission and radar brightness. These data are usually interpreted using electromagnetic models in which volume scattering is the dominant mechanism. The main limitation of this approach is that microwave brightness is not well related to backscatter if the ice sheet is layered. Because larger grain size and thicker annual layers both increase radar image brightness, with the first corresponding to lower accumulation rate and the second to higher accumulation rate, models of radar brightness alone cannot accurately reflect accumulation. Consideration of correlation measurements can also resolve this ambiguity. We introduce an interferometric ice scattering model that relates the interferometric synthetic aperture radar correlation and radar brightness to both ice grain size and hoar layer spacing in the dry-snow zone of Greenland. We use this model and the European Remote Sensing satellite radar observations to derive several parameters related to snow accumulation rates in a small area in the dry-snow zone. These parameters show agreement with four in situ core accumulation rate measurements in this area, whereas models using only radar brightness data do not match the observed variation in accumulation rates. [ABSTRACT FROM AUTHOR]

Characterization of the microwave signature of the Greenland snow surface enables delineation of the different snow facies and is a tool for tracking the effects of climate change. A new empirical observation model is introduced that uses a limited number of parameters to characterize the snow surface based on the dependence of radar backscatter on incidence angle, azimuth angle, spatial gradient, and temporal rate of change. The individual model parameters are discussed in depth with examples using data from the NASA Scatterometer (NSCEF) and from the C-band European Remote Sensing satellite (ERS) Advanced Microwave Instrument in scatterometer mode. The contribution of each model term to the overall accuracy of the model is evaluated. The relative contributions of the modeled dependencies vary by region. Two studies illustrating applications of the model are included. First, interannual changes over the Greenland ice sheet are investigated using nine years of ERS data. Surface changes are observed as anomalies in the σ° model parameters. Second, intra- annual variations of the surface are investigated. These changes are observed in the average backscatter normalized to a given observation geometry. The results indièate that the model can be used to obtain a more complete understanding of multiyear change and to obtain low-variance high temporal resolution Observations of intraannual changes. The model may be applied for increased accuracy in scatterometer, synthetic aperture radar (SAR), and wide- angle SAR studies. [ABSTRACT FROM AUTHOR]

Sea-ice edge detection is an essential task at the different national ice services to secure navigation in ice-covered seas. Comparison between the Remund and Long ice mask image from enhanced-resolution QuikScat/Sea Winds (QS) products and the analyzed ice edge from high-resolution RADARSAT synthetic aperture radar has shown that the automatically determined QS ice mask underestimates the Arctic ice extent. QS data was statistically analyzed by calculating the data with ice charts around Greenland and with the National Aeronautics and Space Administration Team's Special Sensor Microwave/Imager (SSMII) ice concentration algorithm over the whole Arctic region. All variables, i.e., the backscatter in vertical and horizontal polarization, the active polarization ratio (APR) and the daily standard deviation, are sensitive to ice types and are strongly correlated with ice concentration when the relationship is expressed in exponential form. Our study showed that the APR is especially suitable for ice-ocean separation, and a threshold of -0.02 was determined. An ice edge algorithm based on this APR threshold was developed using the other variables with conservative season-dependent thresholds to eliminate additional ocean noise. Also, the history of the ice cover is considered in order to detect single ice fields that are separated from the main Arctic pack ice. Validation with RADARSAT 1 and with the Advanced Very High Resolution Radiometer showed that the new algorithm successfully detects very low ice concentrations of about 10% during the entire year. The validity of the detected ice edge for near-real-time issues is also discussed in relation to the ice motion in the Marginal Ice Zone and the integration time necessary to produce the enhanced-resolution images. The new algorithm improves the automatic global ice edge resolution by a factor of two when compared to SSM/I products and could be used in both model initialization and data assimilation. [ABSTRACT FROM AUTHOR]

Snow accumulation rate is an important parameter in determining the mass balance of polar ice sheets. Accumulation rate is currently determined by analyzing ice cores and snow pits. Inadequate sampling of the spatial variations in the ice sheet accumulation has resulted in accumulation rate uncertainties as large as 24%. We designed and developed a 600-900-MHz airborne radar system for high-resolution mapping of the near-surface internal layers for estimating the accumulation rate of polar ice sheets. Our radar system can provide improved spatial and temporal coverage by mapping a continuous profile of the isochronous layers in the ice sheet. During the 2002 field season in Greenland, we successfully mapped the near-surface layers to a depth of 200 m in the dry-snow zone, 120 m in the percolation zone, and 20 m in the melt zone. We determined the water equivalent accumulation rate at the NASA-U_1 site to be 34.9 ± 5.1 cm/year from 1964 to 1992. This is in close agreement with the ice-core derived accumulation rate of 34.6 cm/year for the same period. [ABSTRACT FROM AUTHOR]