When radar signals penetrate snow and ice, they experience additional delays and directional changes due to the higher refractive index compared to that of air. These propagation effects should be taken into account accurately when processing, simulating, or geocoding radar data. Travel time computation is straightforward when the refractive index is constant, but it becomes challenging in heterogeneous media. This letter introduces novel methods based on the Eikonal equation and Fermat’s principle for efficiently computing radar signal travel times in heterogeneous snow and ice volumes. These approaches can accommodate nearly arbitrary refractive index distributions, ensuring precise handling of propagation effects in radar remote sensing applications.

This paper presents an image formation algorithm for the focusing of SAR data with space-variant impulse response functions caused by eccentric orbits around small high-curvature surfaces, such as is encountered in stable orbits around Saturn’s moon Enceladus, a potential target for future SAR missions such as the Nightingale mission concept under development at JPL. Due to the extreme geometry, the range history shows a significant dependence on the target’s azimuth position within time scales significantly shorter than the synthetic aperture duration. Therefore, additional steps are needed in order to compensate for this effect and minimize image degradation. In this context, the present contribution evaluates the space variance of the geometry for SAR surveys over Enceladus and proposes a processing flow to account for it. Point target simulations using the proposed processing algorithm are shown to verify the approach.

Spaceborne differential SAR interferometry (D-InSAR) has been demonstrated to potentially allow snow water equivalent (SWE) change measurements for dry snow on a spatial scale, resolution, and accuracy unprecedented by other sensor concepts. However, its operational use is hindered mainly because of: 1) low coherence areas resulting from temporal decorrelation, complicating a robust phase unwrapping and 2) an unknown phase offset due to the$2\pi $ambiguity of the interferometric measurement and therefore a strongly biased SWE change estimate. Furthermore, conventional D-InSAR does not provide a direct measurement of the snow density, which is used in the phase-to-SWE inversion and is an important snow parameter. This article presents strategies to potentially overcome these shortcomings by exploiting simultaneously acquired interferograms with different squint angles. The different lines of sight result in differential phase delays introduced by a SWE change. The phase difference between the interferograms may be exploited to produce a low-resolution SWE estimate without the need for phase unwrapping and to resolve the$2\pi $phase ambiguity of the single interferogram. In addition to that, the ratio between the interferograms is a measure of the dielectric permittivity of the snow and can be related to the snow density. The theoretical performance and functionality of the strategies are analyzed for the planned Harmony mission (ESA’s Earth Explorer 10) based on simulated data, indicating great potential of the approach given the large squint diversity of the Harmony constellation.

Single-pass InSAR elevation measurements of dry snow, firn, and ice are known to be substantially biased downward due to a partial penetration of the radar signals into the medium, resulting in a phase center location within the volume. The so-called penetration bias, i.e., the elevation difference between surface and InSAR phase center, can be estimated from the contribution of the volume to the interferometric coherence and may be used to retrieve the surface elevation. In this paper, we show that both an additional elevation bias and a horizontal shift occur in the InSAR processing for natural media with a dielectric constant different to the one of air, originating from an uncompensated stretch of the vertical wavenumber in the medium and refraction effects at the surface. This geolocation error depends on the magnitude of the penetration bias, the dielectric constant, and the acquisition geometry. It may reach up to few meters for X- and C-band frequencies and more for lower frequencies and therefore may significantly affect cryospheric elevation products from past (SRTM), current (TanDEM-X), and future (e.g., Harmony, Tandem-L) SAR interferometers. In this paper, the geolocation error is assessed and an adapted interferometric processing allowing for an accurate geolocation (i.e., surface elevation measurement) is presented.

Plenty of data records demonstrate that differential InSAR acquisitions of snow covered areas are often affected by severe temporal decorrelation, complicating the estimation of snow physical parameters such as the snow water equivalent. The decorrelation effect is commonly attributed to a change in the underlying scattering center distribution due to melting/refreezing, compacting of snow, or redistribution of underlying vegetation. We demonstrate that a mere change of the dielectric constant of a dry snow cover may lead to severe decorrelation, even without a change in scatterer distribution, which provides additional opportunities for the estimation of snow parameters. In this paper, a first discussion of the snow-induced decorrelation effect is provided and the derived model is evaluated against Sentinel-1 12-day coherence data using SWE measurements provided by the Copernicus Global Land Service.

Over the last decades, repeat-pass SAR interferometry (InSAR) for deformation measurement and topographic mapping has revolutionized our understanding of many geophysical processes on Earth. A new mission concept, currently in development at the Jet Propulsion Laboratory (JPL) and Caltech, aims at using orbital repeat-pass InSAR for deformation and topography mapping of Saturn’s ice-covered and geologically active moon Enceladus. In this paper, we present an initial performance assessment of the system and the suggested SAR processing approach, along with simulated InSAR acquisitions using a DLR in-house End-to-End performance simulator.

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.

In the above article[1], references [21] and [29] incorrectly provide the publication years. Reference [21] was published in 2020; reference [29] was published in 2021. The references appear in full here: