Othmar Frey

Focusing of Airborne Synthetic Aperture Radar Data From Highly Nonlinear Flight Tracks

Standard focusing of data from synthetic aperture radar (SAR) assumes a straight recording track of the sensor platform. Small nonlinearities of airborne platform tracks are corrected for during a motion-compensation step while maintaining the assumption of a linear flight path. This paper describes the processing of SAR data acquired from nonlinear tracks, typical of sensors mounted on small aircraft or drones flying at low altitude. Such aircraft do not fly along straight tracks, but the trajectory depends on topography, influences of weather and wind, or the shape of areas of interest such as rivers or traffic routes. Two potential approaches for processing SAR data from such highly nonlinear flight tracks are proposed, namely, a patchwise frequency-domain processing and mosaicking technique and a time-domain back-projection-based technique. Both are evaluated with the help of experimental data featuring tracks with altitude changes, a double bend, a 90deg curve, and a linear flight track. In order to assess the quality of the focused data, close-ups of amplitude images are compared, impulse response functions of a point target are analyzed, and the coherence is evaluated. The experimental data were acquired by the German Aerospace Centers E-SAR L-band system.

Assessment of the influence of flying altitude and scan angle on biophysical vegetation products derived from airborne laser scanning

Airborne Laser Scanning (ALS) has been established as a valuable tool for the estimation of biophysical vegetation properties such as tree height, crown width, fractional cover and leaf area index (LAI). It is expected that the conditions of data acquisition, such as viewing geometry and sensor configuration influence the value of these parameters. In order to gain knowledge about these different conditions, we test for the sensitivity of vegetation products for viewing geometry, namely flying altitude and scanning (incidence) angle. Based on two methodologies for single tree extraction and derivation of fractional cover and LAI previously developed and published by our group, we evaluate how these variables change with either flying altitude or scanning angle. These are the two parameters which often need to be optimized towards the best compromise between point density and area covered with a single flight line, in order to reduce acquisition costs. Our test‐site in the Swiss National Park was sampled with two nominal flying altitudes, 500 and 900 m above ground. Incidence angle and local incidence angle were computed based on the digital terrain model using a simple backward geocoding procedure. We divided the raw laser returns into several different incident angle classes based on the flight path data; the TopoSys Falcon II system used in this study has a maximum scan angle of ±7.15°. We compared the derived biophysical properties from each of these classes with field measurements based on tachymeter measurements and hemispherical photographs, which were geolocated using differential GPS. It was found that with increasing flying height the well‐known underestimation of tree height increases. A similar behaviour can be observed for fractional cover; its respective values decrease with higher flying height. The minimum distance between first and last echo increases from 1.2 metres for 500 m AGL to more than 3 metres for 900 m AGL, which does alter return statistics. The behaviour for incidence angles is not so evident, probably due to the small scanning angle of the system used. fCover seems to be most affected by incidence angles, with significantly higher differences for locations further away from nadir. As expected, incidence angle appears to be of higher importance for vegetation density parameters than local incidence angle.

Analyzing Tomographic SAR Data of a Forest With Respect to Frequency, Polarization, and Focusing Technique

Forest canopies are semitransparent to microwaves at both L- and P-bands. Thus, a number of scattering sources and different types of scattering mechanisms may contribute to a single range cell of a synthetic aperture radar (SAR) image. By appropriately combining the SAR data of multiple parallel flight paths, a large 2-D aperture is synthesized, which allows for tomographic imaging of the 3-D structure of such semitransparent media and the underlying ground. A separate paper deals with the actual tomographic imaging part that leads to the 3-D data cube. In particular, three focusing techniques are described and analyzed: multilook beamforming, robust Capon beamforming, and multiple signal classification beamforming. In this paper, the resulting data products obtained by tomographically focusing two airborne multibaseline SAR data sets of a partially forested area, one at L-band and another at P-band, are subject to a detailed analysis with respect to the location and the type of backscattering sources. In particular, the following aspects are investigated: 1) The forest structure, as obtained from the vertical profiles of intensities at sample plot locations within the forest, is compared to the height distribution of the top of the forest canopy, as derived from airborne laser scanning data, and profiles are presented for all polarimetric channels and focusing techniques, as well as at both frequencies; 2) the type and location of scattering mechanisms are analyzed as functions of height for the two frequencies, namely, L- and P-bands, and using the polarimetric channels, as well as the Pauli and CloudePottier decompositions thereof; and 3) the accuracy of the ground elevation estimation obtained from the different focusing techniques and the two frequencies is assessed with the help of a lidar-derived digital elevation model.

3-D Time-Domain SAR Imaging of a Forest Using Airborne Multibaseline Data at L- and P-Bands

In this paper, a time-domain back-projection based tomographic processing approach to a 3-D reconstruction grid is detailed, with the focusing in the third dimension being either modified versions of multilook standard beamforming, robust Capon beamforming, or multiple signal classification. The novel feature of the proposed approach compared to previous synthetic aperture radar (SAR) tomography approaches is that it allows for an approximation-free height-dependent calculation of the sample covariance matrix by exploiting the azimuth-focused data on the 3-D reconstruction grid. The method is applied to experimental multibaseline quad-pol SAR data at L- and P-bands acquired by German Aerospace Centers (DLR) E-SAR sensor: Tomographic images of a partially forested area, including a 3-D voxel plot that visualizes the very high level of detail of the tomographic image, are shown, and an analysis of the focusing performance is given for the full as well as reduced synthetic aperture in the normal direction.

Measurement of Ionospheric TEC in Spaceborne SAR Data

The propagation of spaceborne radar signals operating at L-band frequency or below can be seriously affected by the ionosphere. At high states of solar activity, Faraday rotation (FR) and signal path delays disturb radar polarimetry and reduce resolution in range and azimuth. While these effects are negligible at X-band, FR and the frequency-dependent path delays can become seriously problematic starting at L-band. For quality assurance and calibration purposes, existing L-band or potential spaceborne P-band missions require the estimation of the ionospheric state before or during the data take. This paper introduces two approaches for measuring the ionospheric total electron content (TEC) from single-polarized spaceborne SAR data. The two methods are demonstrated using simulations. Both methods leverage knowledge of the frequency-dependent path delay through the ionosphere: The first estimates TEC from the phase error of the filter mismatch, while the second gauges path-delay differences between up and down chirps. FR, mean (direct current) offsets, and noise contributions are also considered in the simulations. Finally, possibilities for further methodological improvements are discussed.

Tomographic Imaging of a Forested Area By Airborne Multi-Baseline P-Band SAR

In recent years, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated for airborne L-band data but the quality of the focused tomographic images is limited by several factors. In particular, the common Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. In this paper, a tomographic focusing method based on the time-domain back-projection algorithm is proposed, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. The tomographic focusing quality is assessed by analysing the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, several tomographic slices of a volume representing a forested area are given. The respective P-band tomographic data set consisting of eleven flight tracks has been acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR).

Processing SAR data of rugged terrain by time-domain back-projection

Processing of SAR images of rugged terrain deserves special care because the topography affects the focused image in a number of ways. In order to obtain geometrically and radiometrically corrected SAR images of mountainous areas additional knowledge about the topography and the sensors trajectory and attitude has to be included in the processing or post-processing steps. Various well-known focusing techniques are available to transform SAR raw data into a single look complex image such as the range-Doppler, the chirp scaling or the omega-k algorithm. While these algorithms perform the azimuth focusing step in the frequency domain the time-domain back-projection processing technique focuses the data geometrically, i.e., in the time domain. In contrast to the frequency-domain techniques, time-domain back-projection maintains the entire geometric relationship between the sensor and the illuminated area. This implies a couple of advantages: a stringent, terrain-based correction for the elevation antenna gain pattern may be implemented and topography-induced variation of radar brightness can be eliminated in a single step. Further, the SAR image is focused directly onto an arbitrary reconstruction grid and in the desired geodetic reference frame without requiring any additional processing steps. We discuss the influence of rugged terrain on the radiometric properties of focused SAR data and demonstrate how the time-domain back-projection approach accounts for these effects within one integrated processing framework by incorporating both a correction for terrain slope induced variation of radar brightness and a stringent correction for the elevation antenna gain pattern. The algorithm is evaluated for ENVISAT/ASAR image mode data of a mountainous area.

Tomographic processing of multi-baseline P-band SAR data for imaging of a forested area

Recently, various attempts have been undertaken to obtain information about the structure of forested areas from multi-baseline synthetic aperture radar data. Tomographic processing of such data has been demonstrated but the quality of the focused tomographic image is limited by several factors. In particular Fourier-based focusing methods are susceptible to irregular and sparse sampling, two problems, that are unavoidable in case of multi-pass, multi-baseline SAR data acquired by an airborne system. We propose a tomographic focusing method based on the time-domain back-projection algorithm, which maintains the geometric relationship between the original sensor positions and the imaged target and is therefore able to cope with irregular sampling without introducing any approximations with respect to the geometry. We assess the tomographic focusing quality with the help of the impulse response of simulated point targets and an in-scene corner reflector. And, in particular, preliminary results obtained with the newly acquired P-band tomographic data set consisting of eleven flight tracks are presented.

DEM-Based SAR Pixel-Area Estimation for Enhanced Geocoding Refinement and Radiometric Normalization

Precise terrain-corrected georeferencing of synthetic aperture radar (SAR) images and derived products in range–Doppler coordinates is important with respect to several aspects, such as data interpretation, combination with other geodata products, and transformation of, e.g., terrain heights into SAR geometry as used in differential interferometric SAR (DInSAR) applications. For georeferencing, a lookup table is calculated and then refined based on a coregistration of the actual SAR image to a simulated SAR image. The impact of using two different implementations of such a simulator of topography-induced radar brightness, 1) an approach based on angular relationships and 2) a pixel-area-based method, is discussed in this letter. It is found that the pixel-area-based method leads to considerable improvements with regard to the robustness of georeferencing and also with regard to radiometric normalization in layover-affected areas.

Single-Look SAR Tomography as an Add-On to PSI for Improved Deformation Analysis in Urban Areas

Persistent scatterer interferometry (PSI) is in operational use for spaceborne synthetic aperture radar (SAR)-based deformation analysis. A limitation inherently associated with PSI is that, by definition, a persistent scatterer (PS) is a single dominant scatterer. Therefore, pixels containing signal contributions from multiple scatterers, as in the case of a layover, are typically rejected in the PSI processing, which in turn limits deformation retrieval. SAR tomography has the ability to resolve layovers. This paper investigates the added value that can be achieved by operationally combining SAR tomography with a PSI approach toward the objective of improving deformation sampling in layover-affected urban areas. Different tomographic phase models are implemented and compared as regards their suitability in resolving layovers. Single-look beamforming-based tomographic inversion and a generalized likelihood ratio test (GLRT)-based detection strategy are used to detect single and double scatterers. The quantity of the detected scatterers is weighed against their quality as defined in terms of the phase deviation between the single-look complex (SLC) measurements and the tomographic model fit. The gain in deformation sampling that can be derived with tomography relative to a PSI-based analysis is quantitatively assessed, and alongside the quality of the scatterers obtained with tomography is compared with the quality of the PSs identified with a PSI approach. The experiments are performed on an interferometric stack of 50 TerraSAR-X stripmap images. The results obtained show that, although there is a tradeoff between the quantity and the quality of the detected scatterers, the tested SAR tomography approach leads to an improvement in deformation sampling in layover-affected areas.