Airborne Synthetic Aperture Radar Research Articles

Forest Biomass Retrieval From L-Band SAR Using Tomographic Ground Backscatter Removal

A tomographic synthetic aperture radar (TomoSAR) represents a possible route to improved retrievals of forest parameters. Simulated orbital L-band TomoSAR data corresponding to the proposed Satellites for Observation and Communications-Companion Satellite (SAOCOM-CS) mission (1.275 GHz) are evaluated for retrieval of above-ground biomass in boreal forest. L-band data and biomass measurements, collected at the Krycklan test site in northern Sweden as part of the BioSAR 2008 campaign, are used to compare biomass retrievals from SAOCOM-CS to those based on SAOCOM SAR data. Both data sets are in turn compared with the corresponding airborne case, as represented by experimental airborne SAR through processing of the original SAR data. TomoSAR retrievals use a model involving a logarithmic transform of the volumetric backscatter intensity, $I_{\mathrm{ vol}}$ , defined as the total backscatter originating between 10 and 30 m above ground. SAR retrievals are obtained with slope-compensated intensity $\gamma ^{0}$ using the same model. It is concluded that tomography using SAOCOM-CS represents an improvement over an airborne SAR imagery, resulting in biomass retrievals from a single polarization (HH) having a 26%–30% root-mean-square error with a little to no impact from the look direction or the local topography.

Characterization of L-Band MIMP SAR Data From Rice Paddies at Late Vegetative Stage

Insufficient validation for polarimetric decomposition techniques has led to its less perceived popularity for more than 20 years. The true composition ratio of scattering mechanisms within a radar backscatter should be essential to make polarimetric synthetic aperture radar (SAR) operational applications. To achieve this, a novel comprehensive approach to accurately identify the contribution of each scattering mechanism by a multi-incidence angle and multipolarimetric (MIMP) SAR observation combined with a theoretical model simulation is newly applied to L-band SAR data. Rice paddies in Niigata, Japan having a simple vegetation structure without topography were observed by Polarimetric and Interferometric Airborne SAR L-band 2, by gradually varying the flight path in terms of incidence angle. In addition to the MIMP SAR observation, a dominant scattering mechanism is reliably isolated through the theoretical characterization of the data by a discrete scatterer model. Avoiding unnecessary Bragg scattering effect caused by the methodically distributed rice paddies, the volume scattering from grains is identified as a dominant scattering mechanism over incidence angles. In addition, HH and VV are strongly affected by the double-bounce scattering between stalks and the ground surfaces at only small incidence angles, whereas the contribution of the double-bounce scattering for HV is not obvious. The results at the L-band will be compared with another MIMP SAR data at the X-band obtained for the same rice paddies in 2014 so that multifrequency MIMP SAR data analysis shall be conducted for our next step.

A Coarse-to-Fine Autofocus Approach for Very High-Resolution Airborne Stripmap SAR Imagery

An autofocus operation is an indispensable procedure to obtain well-focused images for synthetic-aperture radar (SAR) systems without precise navigation devices. Three challenges have been faced in the very high-resolution (VHR) airborne SAR autofocus due to the long cumulative time: the varying along-track velocity, the residual range cell migration (RCM), and the range-dependent phase errors with higher order components. When it comes to the stripmap mode, the autofocus becomes more complicated, since the scenario with a few strong scatterers is more likely to be encountered with a moving beam. Combining the merits of parametric and nonparametric autofocus algorithms, a robust motion error estimation method is proposed in this paper. First, we perform a stripmap multiaperture mapdrift autofocus operation to extract the along-track velocity and the most range-invariant errors, removing the residual RCM at a subaperture scale. Second, one referential center block is selected to retrieve the residual range-invariant error, which can eliminate the residual RCM globally in the range dimension. With a global high-quality input, the residual range-variant phase errors can be retrieved precisely utilizing a center-to-edge local maximum-likelihood weighted phase gradient autofocus kernel at last. Experiments on real VHR airborne stripmap SAR data are performed to demonstrate the robustness of the proposed method.

Focusing of Medium-Earth-Orbit SAR Using an ASE-Velocity Model Based on MOCO Principle

The available focusing algorithms for medium-Earth-orbit (MEO) SAR are all based on the complex nonhyperbolic range equation, which may make it more difficult in imaging processing. In this paper, we model the range equation as the standard hyperbolic form based on the motion compensation (MOCO) principle. However, the conventional two-step MOCO may introduce azimuth spectrum expansion due to the potential large motion error, which can lead to severe azimuth ambiguity. To resolve this problem, we develop an omega-K algorithm based on a modified two-step MOCO and an adaptively straight equivalent (ASE)-velocity model. The algorithm is implemented through three-step processing: 1) the modified two-step MOCO does not compensate for the quadratic motion error (the main factor for the spectrum expansion); 2) an ASE-velocity model is introduced to compensate for the quadratic motion error; and 3) an extended Stolt mapping is proposed to perform the accurate range cell migration correction, and the tandem singular value decomposition-nonlinear chirp scaling algorithm is to correct the azimuth-variant phase error and to perform the azimuth compression. Processing of simulated data and airborne SAR real data validates the effectiveness of the proposed algorithm.

Focusing High-Resolution Highly-Squinted Airborne SAR Data with Maneuvers

Maneuvers provide flexibility for high-resolution highly-squinted (HRHS) airborne synthetic aperture radar (SAR) imaging and also mean complex signal properties in the echoes. In this paper, considering the curved path described by the fifth-order motion parameter model, effects of the third- and higher-order motion parameters on imaging are analyzed. The results indicate that the spatial variations distributed in range, azimuth, and height directions, have great impacts on imaging qualities, and they should be eliminated when designing the focusing approach. In order to deal with this problem, the spatial variations are decomposed into three main parts: range, azimuth, and cross-coupling terms. The cross-coupling variations are corrected by polynomial phase filter, whereas the range and azimuth terms are removed via Stolt mapping. Different from the traditional focusing methods, the cross-coupling variations can be removed greatly by the proposed approach. Implementation considerations are also included. Simulation results prove the effectiveness of the proposed approach.

Efficient Space-Variant Motion Compensation Approach for Ultra-High-Resolution SAR Based on Subswath Processing

Motion compensation (MOCO) is essential to obtain high-quality images for airborne synthetic aperture radar (SAR). In the case of ultrahigh resolution, how to compensate the space-variant motion errors accurately and efficiently is still a great challenge. An improved space-variant MOCO scheme is presented in this paper, taking into account both precision and efficiency. By subswath processing, an approximate range envelope compensation without interpolation can be implemented efficiently. Meanwhile, to correct the range-variant component of motion errors effectively, the conventional MOCO processing flow should be modified, guaranteeing that the phase compensation of the one-step MOCO algorithm is not affected by the approximate range envelope compensation. Moreover, based on subswath processing, the range variance of residual azimuth-variant errors can also be degraded, as well as the influence of that on azimuthal time–frequency relationship. Thus, the focusing effect in the case of wide beam is improved significantly, and the computational burden of the precise topography- and aperture-dependent (PTA) algorithm is also reduced. The proposed approach is useful in practice, and the resolution of image corrected by this approach attains 0.1 m. Simulations with point targets and processing of real data have validated the proposed approach.

A Novel Approach of Slope Detection Combined with Lv’s Distribution for Airborne SAR Imagery of Fast Moving Targets

This paper presents a fast SAR imagery algorithm for Ground Moving Target Imaging (GMTIm) based on the slope detection strategy combined with Time-Frequency Representation (TFR), which is known as Lv’s Distribution (LVD). This fast imagery algorithm focuses on the solution of the ambiguity problems and relevant heavy computing load in SAR imagery. Firstly, according to the relationship between the slope of the range walk trajectory and the cross-track velocity of moving target, a new high-efficiency slope detection strategy based on gradient and level-line angle is presented in the image domain. Then, the Doppler centroid shift induced by cross-track velocity can also be obtained. Secondly, owing to the cross-track velocity estimated before, the Range Walk Migration Correction (RWMC) can be performed to concentrate the echo response of the moving target into a single range cell. Finally, due to the superior performance in representing multi-component Linear Frequency Modulation (LFM) signal, LVD is adopted here to represent the Doppler chirp rate of multiple moving targets in a Doppler Centroid Frequency and Chirp Rate domain (CFCR). The performance of the proposed algorithm is evaluated in terms of superiority and effectiveness using simulations, and the comparison between the proposed algorithm and the other conventional algorithms is also presented.

Inferring surface currents within submerged, vegetated deltaic islands and wetlands from multi-pass airborne SAR

Water flow patterns across coastal and deltaic wetlands affect biogeochemical cycling, denitrification, organic carbon burial, and coastal landscape evolution. Our understanding of such patterns across these important landscapes is incomplete, however, because of the inherent difficulty of conducting spatially and temporally dense ground- or boat-based surveys in shallow, vegetated terrain. We conducted an airborne L-band synthetic aperture radar (SAR) acquisition campaign on Wax Lake Delta, Louisiana, USA, in May 2015, to investigate whether water velocities and flow patterns over kilometer scales can be determined from remote sensing. Thirteen SAR flight lines over the delta region were acquired in 3 h with six different flight directions, concurrently with a small boat campaign. We show that SAR azimuth displacement due to Doppler shift can be used to estimate the surface water flow relative to the static and submerged vegetation interspersed on delta islands, using a simple Bragg wave scattering model and accounting for the Bragg wave's free velocity and wind drift. At Wax Lake Delta, we find that ~0.40 m/s water velocities within the main deltaic channels slow to 0.1–0.2 m/s as flow spreads laterally across, and converges within, the vegetated islands, coinciding with shallow (<0.5 m) depths and heightened flow resistance. This SAR-based technique opens up new avenues for understanding shallow submerged, vegetated coastal wetlands and deltas.

DESPECKLING POLSAR IMAGES BASED ON RELATIVE TOTAL VARIATION MODEL

Abstract. Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

HIGH RESOLUTION SAR IMAGING EMPLOYING GEOMETRIC FEATURES FOR EXTRACTING SEISMIC DAMAGE OF BUILDINGS

Abstract. Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover &amp;amp; bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.

TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

Abstract. Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE

Abstract. In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.

Raw Data-Based Motion Compensation for High-Resolution Sliding Spotlight Synthetic Aperture Radar.

For accurate motion compensation (MOCO) in airborne synthetic aperture radar (SAR) imaging, a high-precision inertial navigation system (INS) is required. However, an INS is not always precise enough or is sometimes not even included in airborne SAR systems. In this paper, a new, raw, data-based range-invariant motion compensation approach, which can effectively extract the displacements in the line-of-sight (LOS) direction, is proposed for high-resolution sliding spotlight SAR mode. In this approach, the sub-aperture radial accelerations of the airborne platform are estimated via a well-developed weighted total least square (WTLS) method considering the time-varying beam direction. The effectiveness of the proposed approach is validated by two airborne sliding spotlight C band SAR raw datasets containing different types of terrain, with a high spatial resolution of about 0.15 m in azimuth.

Atmospheric Phase Screen in GEO-SAR: Estimation and Compensation

We study the impact of atmospheric turbulence, specifically the wet tropospheric delay, in that synthetic aperture radar (SAR) with very long integration time, from minutes to hours, and wide swaths, such as the geosynchronous or geostationary SAR. In such systems, the atmospheric phase screen (APS) cannot be assumed frozen in time as for Low Earth Orbit or airborne SARs nor constant in space as for the ground-based SAR. The impact of space–time turbulence on SAR focusing is quantitatively assessed, and a novel focusing method that integrates APS estimation and compensation is proposed. Performances are evaluated as a function of SAR parameters, mainly the wavelength, based on a parametric model of the APS variogram, and results achieved by a simulating realistic scenario are shown.

Coherent Auto-Calibration of APE and NsRCM under Fast Back-Projection Image Formation for Airborne SAR Imaging in Highly-Squint Angle

Synthetic Aperture Radar (SAR) imaging with a non-zero (forward) squint angle is capable of providing a longer time for reaction than that of the broadside mode. However, due to the large squint angle, there will be severe coupling between range and azimuth samples in the echoed data, which is known as the problematic Range Cell Migration (RCM) in the SAR community. Especially when the SAR sensor mounted on an airborne platform encounters unexpected motion deviations/errors, the coupling becomes more complicated, and it is difficult to differentiate the systematic RCM for the SAR Image Formation Processing (IFP) and the non-systematic RCM error to be compensated. To this end, a novel and accurate SAR imaging algorithm is proposed in this paper to facilitate the processing of airborne SAR data collected at a high-squint angle. Firstly, the proposed algorithm is established under a Fast Time-Domain Back-Projection (FTDBP) framework for the SAR IFP. FTDBP paves the way to avoid the complicated processing for the systematic RCM as for the conventional SAR IFP in the Doppler processing manner. It is capable of generating a high-resolution SAR image efficiently under more general geometries and configurations. Secondly, regarding the non-systematic RCM errors, the proposed algorithm realizes the compensation by correcting both the Non-systematic Range Cell Migration (NsRCM), as well as Azimuthal Phase Error (APE) in a coherent manner. It is consequently capable of auto-calibrating the effects of the motion error completely without being dependent on the airborne navigation unit. Finally, both simulated and raw data collected by the airborne squinted SAR are applied to evaluate the proposed algorithm. Comparisons with conventional algorithms are carried out to reveal the superiority of the proposed algorithm.

Local region power spectrum-based unfocused ship detection method in synthetic aperture radar images

Ships on synthetic aperture radar (SAR) images will be severely defocused and their energy will disperse into numerous resolution cells under long SAR integration time. Therefore, the image intensity of ships is weak and sometimes even overwhelmed by sea clutter on SAR image. Consequently, it is hard to detect the ships from SAR intensity images. A ship detection method based on local region power spectrum of SAR complex image is proposed. Although the energies of the ships are dispersed on SAR intensity images, their spectral energies are rather concentrated or will cause the power spectra of local areas of SAR images to deviate from that of sea surface background. Therefore, the key idea of the proposed method is to detect ships via the power spectra distortion of local areas of SAR images. The local region power spectrum of a moving target on SAR image is analyzed and the way to obtain the detection threshold through the probability density function (pdf) of the power spectrum is illustrated. Numerical P- and L-band airborne SAR ocean data are utilized and the detection results are also illustrated. Results show that the proposed method can well detect the unfocused ships, with a detection rate of 93.6% and a false-alarm rate of 8.6%. Moreover, by comparing with some other algorithms, it indicates that the proposed method performs better under long SAR integration time. Finally, the applicability of the proposed method and the way of parameters selection are also discussed.

Comparison of Freeboard Retrieval and Ice Thickness Calculation From ALS, ASIRAS, and CryoSat‐2 in the Norwegian Arctic to Field Measurements Made During the N‐ICE2015 Expedition

AbstractWe present freeboard measurements from airborne laser scanner (ALS), the Airborne Synthetic Aperture and Interferometric Radar Altimeter System (ASIRAS), and CryoSat‐2 SIRAL radar altimeter; ice thickness measurements from both helicopter‐borne and ground‐based electromagnetic‐sounding; and point measurements of ice properties. This case study was carried out in April 2015 during the N‐ICE2015 expedition in the area of the Arctic Ocean north of Svalbard. The region is represented by deep snow up to 1.12 m and a widespread presence of negative freeboards. The main scattering surfaces from both CryoSat‐2 and ASIRAS are shown to be closer to the snow freeboard obtained by ALS than to the ice freeboard measured in situ. This case study documents the complexity of freeboard retrievals from radar altimetry. We show that even under cold (below −15°C) conditions the radar freeboard can be close to the snow freeboard on a regional scale of tens of kilometers. We derived a modal sea‐ice thickness for the study region from CryoSat‐2 of 3.9 m compared to measured total thickness 1.7 m, resulting in an overestimation of sea‐ice thickness on the order of a factor 2. Our results also highlight the importance of year‐to‐year regional scale information about the depth and density of the snowpack, as this influences the sea‐ice freeboard, the radar penetration, and is a key component of the hydrostatic balance equations used to convert radar freeboard to sea‐ice thickness.

Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

A method of estimating the velocity of moving targets for use in high-resolution wide-swath SAR imaging

ABSTRACTHigh-resolution wide-swath (HRWS) synthetic aperture radar (SAR) systems utilize multiple along-track channels to collect additional samples under relatively low pulse repetition frequency (PRF). This manuscript focuses on cross-track velocity estimation of a moving target in HRWS SAR, since this information is an important input parameter to HRWS non-uniform reconstruction and focusing of a moving target. However, velocity estimation in HRWS SAR would face the problems of the Doppler ambiguous image due to under-sampled data in the single channel. In this manuscript, the velocity of a moving target is modeled as phase offset vector. And then the problem of estimating velocity is transformed to find the optimal solution of the proposed cost function. The simulations are conducted to evaluate the performance and effectiveness under different along-track velocities, signal-to-noise ratios, and clutter models. The proposed method is also validated using airborne SAR data with four along-track channels.

Initial Evaluation of SAR Capabilities in UAV Multicopter Platforms

Airborne synthetic aperture radar (SAR) sensors have been commonly used during the last decades to monitor different phenomena in medium-scale areas of observation, such as object detection and characterization or topographic mapping. The use of unmanned aerial vehicles (UAVs) is a cost-effective solution that offers higher operational flexibility than airborne systems to monitor these types of scenarios. The Universitat Politecnica de Catalunya has developed the first fully polarimetric SAR system at X-band integrated into a small UAV multicopter platform (UAV MP). The sensor, called AiR-based remote sensing, has been integrated into the platform overcoming restrictions of weight, space, robustness, and power consumption. To demonstrate the validity of the developed system, some measurement campaigns have been conducted in the outskirts of Barcelona, Spain.