Multibaseline Synthetic Aperture Radar Data Research Articles

A Novel Phase Compensation Method for Urban 3D Reconstruction Using SAR Tomography

Synthetic aperture radar (SAR) tomography (TomoSAR) has been widely used in the three-dimensional (3D) reconstruction of urban areas using the multi-baseline (MB) SAR data. For urban scenarios, the MB SAR data are often acquired by repeat-pass using the spaceborne SAR system. Such a data stack generally has long time baselines, which result in different atmospheric disturbances of the data acquired by different tracks. These factors can lead to the presence of phase errors (PEs). PEs are multiplicative noise for observation data, which can cause diffusion and defocus in TomoSAR imaging and seriously affect the extraction of target 3D information. In this paper, we combine the methods of the block-building network (BBN) and phase gradient autofocus (PGA) to propose a novel phase compensation method called BBN-PGA. The BBN-PGA method can effectively and efficiently compensate for PEs of the MB SAR data over a wide area and improve the accuracy of 3D reconstruction of urban areas. The applicability of this proposed BBN-PGA method is proved by using simulated data and the spaceborne MB SAR data acquired by the TerraSAR-X satellite over an area in Barcelona, Spain.

Forest height retrieval using P-band airborne multi-baseline SAR data: A novel phase compensation method

Synthetic aperture radar (SAR) tomography (TomoSAR) has been well-established for three-dimensional (3-D) information extraction of forests using the multi-baseline SAR data stacks. The multi-baseline SAR data stacks can be acquired by spaceborne and airborne SAR systems, but for forest scenarios, the data stacks acquired by the airborne SAR system are mostly used. Such a data stack has the advantages of short revisiting time and weak temporal decorrelation. However, due to the baseline errors (caused by the residual platform motion and the measurement errors of the navigation instruments), phase errors (PEs) will occur. PEs are independent of one track to the other, resulting in spreading and defocusing in tomographic imaging. In this paper, we proposed a novel phase compensation method named NC-PGA, which combines the methods of network construction (NC) and phase gradient autofocus (PGA) to estimate and compensate the PEs. The NC method uses the Delaunay triangulation network and beamforming to obtain an accurate elevation estimate of the selected permanent scatterers, which can be used as the prior information for subsequent processing to overcome the shortcomings of the PGA method in PEs estimation. The PGA method uses the spatial invariance of PEs in a limited area to compensate for the PE of each track. The applicability of the NC-PGA method is demonstrated using simulated data and real data. The real data contains two data stacks. The one is acquired by a full-polarization P-band airborne SAR system (developed independently by our project research team) over the study area in Saihanba Forest Farm in Hebei, China. The other one is acquired by ONERA SETHI airborne system over Paracou, French Guiana, in the frame of the European Space Agency’s campaign TropiSAR. We select a test area in the study area and successfully retrieve the height of the forest, and use LiDAR data for results validation and evaluation.

A Modified Capon Method for SAR Tomography Over Forest

The 3-D structure of forests is an important indicator for evaluating forest health and can provide data support for ecological monitoring and protection. Synthetic aperture radar (SAR) tomography (TomoSAR) is an important technology for forest structure estimation using the multibaseline (MB) SAR data stacks. The spectral estimators, such as the Capon method, are usually used to estimate the 3-D reflectivity along elevation direction. In this letter, a modified Capon (M-Capon) method is proposed to improve the estimated profiles of ground and canopy scatterers in the elevation direction, including the estimation accuracy and resolution. This method combines the ideas of the CLEAN algorithm with the Capon method and uses iteration to improve the resolution and accuracy of the estimation. The effectiveness of the M-Capon method is demonstrated using the simulated data and the MB SAR data acquired by the P-band airborne SAR system over the Saihanba Forest Farm in Hebei, China.

Tropical Forest Height Retrieval Based on P-Band Multibaseline SAR Data

In this letter, we present an experimental assessment of vegetation height retrieval in tropical forests based on P-band synthetic aperture radar (SAR) acquisitions. Two approaches are implemented and compared: 1) parametric height estimation by minimizing the least-square problem between random volume over ground (RVoG) model predictions and multibaseline SAR data and 2) thresholding the vertical backscattering profiles that are focused by SAR Beam-forming tomography. The data set under analysis is from the ESA AfriSAR campaign that was flown over Gabon in 2016. Results show that at a resolution of $25~\text{m}\times 25~\text{m}$ , which corresponds to about 80 independent looks, both of the two approaches are able to retrieve forest height to within an accuracy of about 3 m or better over the interval of forest height between 30 and 50 m when compared to Light Detection and Ranging (LiDAR) measurements.

Sensitivity of SAR Tomography to the Phenological Cycle of Agricultural Crops at X-, C-, and L-band

Understanding the impact of soil and plant parameter changes in agriculture on Synthetic Aperture Radar (SAR) measurements is of great interest when it comes to monitor the temporal evolution of agricultural crops by means of SAR. In this regard, specific transitions between phenological stages in corn, barley, and wheat have been identified associated to certain dielectric and geometric changes, based on a time series of fully polarimetric multibaseline SAR data and in situ measurements. The data have been acquired in the frame of DLR's CROPEX campaign on six dates between May and July in 2014. The experiments reported in this paper address the sensitivity of X-, C-, and L-band to phenological transitions exploiting the availability of multiple baselines on each acquisition date. The application of tomographic techniques enables the estimation of the three-dimensional (3-D) backscatter distribution and the separation of ground and volume scattering components. Tomographic parameters have been derived at different frequencies, namely the center of mass of the profiles of the total and of the volume-only 3-D backscatter, and the ground and volume powers. Their sensitivity and ability to detect changes occurring on the ground and in the vegetation volume have been evaluated focusing on the added value provided by the 3-D resolution at the different frequencies and polarizations available.

3-D Scattering Characterization of Agricultural Crops at C-Band Using SAR Tomography

The aim of this paper is to interpret and characterize the changes of the 3-D polarimetric scattering signatures of agricultural crops at C-band and to relate them to temporal changes of the soil and plant parameters. For this, a time series of multibaseline (MB) synthetic aperture radar (SAR) data acquired at C-band by the airborne F-SAR system of the German Aerospace Center over the Wallerfing test site in Germany was analyzed. The availability of MB SAR data enables the resolution of scattering contributions in height by means of SAR tomography. The tomographic profiles at different polarizations were analyzed regarding temporal changes for different crop types. First, it was investigated if the center of mass (CoM) of the vertical reflectivity profiles as a single parameter enables the tracking of changes in soil and vegetation. The results show that the vertical reflectivity profiles and their CoM do not allow resolving the ambiguity if a change originates from soil or vegetation dynamics as expected. Thus, the scattering contributions from ground and volume were separated in height, using a filtering approach, and used for the estimation of the ground and volume scattering powers by means of covariance matching. Comparing the outputs with coincident ground measurements showed that dielectric as well as geometric changes in the vegetation are traceable by the separated ground and volume powers. Finally, the estimated powers were analyzed with respect to orientation effects, i.e., to polarimetric anisotropic behavior. They were found to be not significant for the crops under study at C-band.

On the Separation of Ground and Volume Scattering Using Multibaseline SAR Data

In forest and agricultural scattering scenarios, the backscattered synthetic aperture radar (SAR) signature consists, depending on the frequency, of the superposition of ground and volume scattering contributions. Using multibaseline SAR data, SAR tomography techniques allow resolving contributions occurring at different heights. Two algorithms for the separation of ground and volume scattering are compared with respect to their ability to provide a coherent volume component that can be further used for parameter inversion, both of them requiring only the a priori known ground topography. Once the volume-only coherences are available, the total ground and volume scattering powers are estimated by means of a least squares fitting. The objective of this letter is to quantitatively evaluate the performance of this estimation by means of a Monte Carlo analysis with simulated data focusing on the impact of vertical resolution, errors in the knowledge of the ground topography and phase calibration residuals.

Maximum‐likelihood‐based approach for single‐pass synthetic aperture radar tomography over urban areas

Synthetic aperture radar (SAR) tomography (TomoSAR) is one of the key techniques in remote sensing for a sophisticated, three-dimensional (3D) analysis of complex scenes such as forests or urban areas. During recent years, much progress has been made in order to deal with unfavourable data conditions and to further enhance the achievable resolutions. Since TomoSAR has essentially be seen as a spectral estimation problem in the context of array signal processing, most of the methods investigated until now rely on a relatively large tomographic aperture and a relatively high number of receiving antennas in order to be able to separately reconstruct scatterers below the Rayleigh resolution limit. In contrast to that, this study proposes a maximum-likelihood-based approach for tomographic SAR inversion, which provides a better height resolution than conventional array signal processing approaches even if the number of antennas or the overall baseline size is limited. The algorithm is tested on real multi-baseline SAR data acquired over an urban area by an airborne single-pass four-antenna system operating in the millimetre-wave domain. First results show the feasibility of the method both with respect to 3D scatterer reconstruction and 3D SAR focusing.

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.

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).