Conference Agenda

Provided that there is enough penetration in the medium, multibaseline interferometric acquisitions can be used to reconstruct the vertical profile of the scene via its power spectral density [1]. This technique, known as radar tomographic imaging, is particularly advantageous because it does not alter the volume of interest and provides information from the whole scene, contrasting with other methods that only retrieve a profile for a single datapoint. [2,3]

We have conducted our tomographic experiment with KAPRI, a Ku-band ground-based interferometer with full-polarimetric capabilities [4]. In order to create a tomographic array, it was necessary to use two KAPRI devices (G21 and G22) operating in bistatic mode. The devices were placed in different locations, resulting in a separation of a few-meters in the horizontal and vertical directions that together with the local geometry determined the effective baseline. The KAPRI units were used sequentially. First, the G21 acted as both transmitter and receiver (master) while G22 was used as passive receiver only (slave). In the next step, the devices exchanged roles. The temporal baseline between transmissions was kept below 3 minutes, which allowed to consider consecutive acquisitions as simultaneous, hence, increasing the density of the tomographic array.

The tomographic imaging was performed in two locations. The first campaign took place in mid-February, a five-hour long time series were retrieved from the Jungfraufirn region (Aletschglacier, Switzerland), in a flat and homogeneous snow-covered region of the glacier. Additionally to the radar measurements, in-situ glacier investigations were done as a support for later data processing and interpretation. The complementary fieldwork consisted of installing two corner reflectors on the glacier surface for radar measurements, snow-depth investigations, recording the temperature and density of snow, taking images of snow grains and using a metallic scatterer inside the snowpack for depth penetration estimation. A second campaign was done in ETH Hönggerberg on a meadow area with the purpose of helping with the processing of the previous dataset and investigating decorrelation phenomena of unclear source on the Jungfraujoch campaign.

The data pre-processing is proving to be particularly challenging given the fact that Ku-Band has such a small wavelength (1.74cm) and makes the system very sensitive to small inaccuracies of the horizontal baseline. Thus, making the coregistration step very time consuming. Furthermore, the temporal baseline, despite being so small, is enough to cause decorrelation at this wavelength, in turn, resulting into noisy interferograms. Such problem had to eventually be solved by using very strong adaptive filtering (Goldstein filter).

Even though preprocessing is still on-going, there are results that are valuable due to the lack of investigations of different media using Ku-Band. Our specific radar configuration leads to a narrow “usable” region of the scene due to horizontal decorrelation. However, this limitation allows us to observe that the snow and vegetation datasets exhibit different decorrelation behaviors. We interpret this as the meadows behaving closer to a surface scatterer while the snowpack to a volume scatterer. Further analysis of the dataset will determine if the volume information contained in the radar signal can be exploited to reconstruct the vertical profile.

References

[1] Stoica, P., & Moses, R. L. (2005). Spectral Analysis of Signals. Prentice Hall.

[2] Tebaldini, S., et al. (2013). High-resolution 3D imaging of a snowpack from ground-based SAR at X and Ku band. IGARSS.

[3] Frey, O., et al. (2023). Time-series analysis of snow vertical profiles by SAR tomography at L/S/C, Ku, and Ka bands vs. snow characterization. IGARSS, 754–757.

[4] Werner, C., et al. (2012). The GPRI multi-mode differential interferometric radar for ground-based observations. EUSAR, 304–307.