High-resolution Airborne Synthetic Aperture Radar Research Articles

Studies on High-Resolution Airborne Synthetic Aperture Radar Image Formation with Pseudo-Random Agility of Interpulse Waveform Parameters

By means of alteration of the transmitted linear frequency modulation (LFM) signal waveform parameters, such as pulse width or chirp rate, initial phase, pulse repetition interval (PRI), and chirp rate polarity at every position of synthetic apertures, the pseudo-random agility technology of interpulse waveform parameters in airborne Synthetic Aperture Radar (SAR) actively increases the complexity and uncertainty of radar waveforms. This technology confuses jamming interception receivers, thus improving its anti-interference ability for active coherent jamming, which is one of the main research interests of airborne SAR technology. But the pseudo-random agility technology for interpulse waveform parameters faces certain challenges of large computation and complex system design, which need to be further studied and solved. To address these issues, a processing scheme of high-resolution SAR image formation which is appropriate for agile interpulse waveform parameters is proposed in this paper. This method can deal with multiple agile parameters, not only single ones as in most existing literature. Its computation load is nearly comparable to that of traditional SAR image formation with constant waveform parameters. The high-resolution SAR imaging results obtained by processing SAR raw data with agile interpulse waveform parameters demonstrate the effectiveness of the proposed method. In addition, real SAR images with resolutions of 0.5 m and 0.15 m, which are rarely found in the public literature, are shown under the circumstance of randomly changing the transmitted wideband LFM signal pulse parameters one by one.

A High-Resolution Airborne SAR Autofocusing Approach Based on SR-PGA and Subimage Resampling With Precise Hyperbolic Model

High-resolution airborne synthetic aperture radar (SAR) imaging requires long synthetic aperture time (LSAT). However, the LSAT invalidates the Fresnel approximation in the traditional autofocusing method, leaving a residual signal phase in the motion error. To solve the problem, a signal-reconstruction-based phase gradient autofocus (SR-PGA) and a sub-image resampling (SIR) methods are proposed. They are developed on the hyperbolic model. First, a sub-aperture division strategy divides the full-aperture high-order error into multiple low-order sub-aperture errors. Then, the SR-PGA is developed to estimate the sub-aperture error (SPE), in which the precise deramping is reconstructed to eliminate the residual signal phase in the SPE. Third, the SIR is proposed to eliminate residual Doppler-variant shift of the adjacent sub-images, improving the accuracy of the SPE combination. Finally, simulation and actual data processing verify the effectiveness and validity of the algorithm.

Enhanced compressed sensing autofocus for high-resolution airborne synthetic aperture radar

The limited accuracy of the navigation system leads to deviations between the real and measured trajectories in airborne synthetic aperture radar (SAR) which results in residual motion (phase) errors and seriously degrades the image quality. The residual errors are usually corrected by using autofocus methods. In this paper, we investigate the autofocus for a high-resolution airborne SAR system which employs stepped-frequency chirp (SFC) signal to achieve high range resolution. As a promising waveform to improve radar range resolution, the SFC signal is widely realized in practical systems. We characterize the backscattering from the scene, phase errors, and receiver noise with a linear matrix-based formulation. In addition, we propose a compressed sampling method that is directly applied to the scene and received signal to provide a sparse raw dataset. We describe the autofocus problem as a constrained optimization problem and propose a new compressed sensing (CS)-based autofocus method to solve it. This method iteratively estimates the phase error and reconstructs the high-resolution SAR image. The image reconstruction is based on the proximity algorithm which applies the shrinkage proximal operator to solve the problem in a computationally efficient manner. We validate the effectiveness of the proposed method using both simulated and real SAR images. Based on visual results and a variety of metrics, the proposed method outperforms the classical autofocus approaches. Also, it provides better or comparable results, with much lower computational complexity, in comparison to that of the recent CS-based autofocus methods.

2-D Spatially Variant Motion Error Compensation for High-Resolution Airborne SAR Based on Range-Doppler Expansion Approach

Motion errors are inevitable in real-world scenarios and introduce significant phase errors in airborne synthetic aperture radar (SAR) imaging. Generally, these errors consist of the cross-coupling and spatially variant components. Cross-coupling errors can usually be eliminated by motion compensation (MoCo), whereas the latter are seldom addressed, which deteriorate the imaging qualities, especially for the high-resolution cases. To solve the problem, a novel approach based on 2-D range-Doppler expansion is proposed. First, an accurate range equation of the aircraft is obtained based on the inertial navigation system (INS) data. Then, the range-Doppler expansion corresponding to the slant range and Doppler centroid are performed, by which the echo signal is decoupled into two spatially variant parts in range and azimuth directions. Finally, the chirp-z transforms (CZTs) are employed to remove the range and azimuth spatial variations introduced, respectively, by the cross-track and along-track errors. Different from the conventional methods, our approach can greatly decrease the cross-coupling and spatially variant effects brought by motion errors in high-resolution cases. Computer simulation and real data experiments demonstrate the effectiveness of the proposed approach.

Sea Spike Suppression Method Based on Optimum Polarization Ratio in Airborne SAR Images.

In the condition of ocean observation for high-resolution airborne synthetic aperture radar (SAR), sea spikes will cause serious interference to SAR image interpretation and marine target detection. In order to improve the ability of target detection, it is necessary to suppress sea spikes in SAR images. However, there is no report on sea spike suppression methods in SAR images. As a step forward, a sea spike suppression method based on optimum polarization ratio in airborne SAR images is proposed in this paper. This method is only applicable to the situation where VV and HH dual-polarized SAR data containing sea spikes are acquired at the same time. By calculating the optimum polarization ratio, this method further obtains the difference image of the panoramic area accomplishing sea spike suppression. This method is applied to a field airborne X-band SAR data, including ocean waves, oil spills and ships. The results show that the sea spikes are well suppressed, the contrast of ocean waves and the contrast of oil spills are improved, and the false alarm rate of ship detection is reduced. The discussions on these results demonstrate that the proposed method can effectively suppress sea spikes and improve the interpretability of SAR images.

An Extended Two Step Approach to High-Resolution Airborne and Spaceborne SAR Full-Aperture Processing

The processing of synthetic aperture radar (SAR) echoes collected during radar antenna beam steering, such as in the staring spotlight, sliding spotlight, and TOPS operating modes, requires additional efforts due to the limited pulse repetition frequency (PRF). Subaperture processing is mostly used in these cases, but the complexity arising from subaperture dividing and recombination is preferably avoided. The two-step approach (TSA) is an elegant solution to full-aperture processing. Nevertheless, for high-resolution airborne and spaceborne SAR processing, the TSA is still faced with a number of difficulties, which does not occur, however, in subaperture processing. For instance, the high range bandwidth induces Doppler spectrum aliasing during the spectral analysis (SPECAN) stage of the original TSA. Moreover, the Doppler spectrum obtained in TSA, when inverse Fourier transformed back to the slow time domain, might also suffer from aliasing, which precludes the estimation and correction of the unknown residual motion error or tropospheric disturbance. In this article, we extend the TSA to address these problems and present a full-aperture processing framework to precisely focus the high-resolution airborne and spaceborne SAR data. Simulation of X-band spaceborne SAR echoes with transmission signal bandwidth of 3.6 GHz and coherent integration angle of 12.5° has validated the extended TSA (ETSA). Meanwhile, experimental X-band airborne SAR data with the same range and azimuth resolution are also processed using the ETSA, where the conventional autofocusing techniques have been smoothly incorporated.

The High-Resolution Digital-Beamforming Airborne SAR System DBFSAR

Synthetic Aperture Radar (SAR) is an established remote sensing technique that can robustly provide high-resolution imagery of the Earth’s surface. However, current space-borne SAR systems are limited, as a matter of principle, in achieving high azimuth resolution and a large swath width at the same time. Digital beamforming (DBF) has been identified as a key technology for resolving this limitation and provides various other advantages, such as an improved signal-to-noise ratio (SNR) or the adaptive suppression of radio interference (RFI). Airborne SAR sensors with digital beamforming capabilities are essential tools to research and validate this important technology for later implementation on a satellite. Currently, the Microwaves and Radar Institute of the German Aerospace Center (DLR) is developing a new advanced high-resolution airborne SAR system with digital beamforming capabilities, the so-called DBFSAR, which is planned to supplement its operational F-SAR system in near future. It is operating at X-band and features 12 simultaneous receive and 4 sequential transmit channels with 1.8 GHz bandwidth each, flexible DBF antenna setups and is equipped with a high-precision navigation and positioning unit. This paper aims to present the DBFSAR sensor development, including its radar front-end, its digital back-end, the foreseen DBF antenna configuration and the intended calibration strategy. To analyse the status, performance, and calibration quality of the DBFSAR system, this paper also includes some first in-flight results in interferometric and multi-channel marine configurations. They demonstrate the excellent performance of the DBFSAR system during its first flight campaigns.

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 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.

Extended Autofocus Backprojection Algorithm for Low-Frequency SAR Imaging

Since the trajectory deviations of a radar platform cause serious phase errors that degrade the focusing quality of synthetic aperture radar (SAR) imagery, an autofocus method is very important for high-resolution airborne SAR imaging. In this letter, an extended autofocus backprojection (EABP) algorithm is developed to accommodate the phase errors. Under the criterion of maximum image sharpness, the traditional ABP algorithm supports a broader class of collection and imaging geometries. However, it neglects the influence of SAR image energy distribution on the estimation of phase errors that make it inapplicable for SAR imaging, which has high dynamic range, such as low-frequency SAR imaging. By choosing regions and balancing the energy distribution of the data, the EABP algorithm is more efficient and useful to avoid the estimation error caused by the unbalanced energy distribution. Its performance has been demonstrated by using the experimental data that are acquired by a P-band airborne SAR system with a low-accuracy global positioning system.

Precise aperture‐dependent motion compensation for high‐resolution synthetic aperture radar imaging

Aperture-dependent motion compensation (MOCO) is crucial for high-resolution airborne synthetic aperture radar (SAR) imaging, which can suppress image degradation especially for SAR systems working at a high-frequency waveband, such as millimetre-wave (MMW) SAR. The current precise topography and aperture (PTA) dependent MOCO algorithm aims to compensate the azimuth-dependent motion error by using a modified azimuth matched filtering. However, the matched filter is deduced with the principle of stationary phase without considering the effects from the azimuth-dependent motion errors, which limits its precision in focusing MMW SAR data involving severe motion errors. This study proposes a refined PTA algorithm with a precise post matched filter established by the method of series reversion. The range-variant characteristic of residual motion errors is also investigated for an improved precision. Simulated and real MMW SAR data sets are used to validate the effectiveness of the proposal.

Range cell migration correction analysis of one-step and two-step motion compensation for millimeter-wave airborne SAR imaging

Conventional two-step motion compensation (MOCO) method is widely adapted for airborne synthetic aperture radar (SAR) imaging due to its conciseness combining with the SAR focusing procedure. For two-step MOCO, range-independent compensation is processed before range cell migration correction (RCMC), and the range-dependent phase correction is implemented after RCMC. However, the accuracy of RCMC would be seriously decreased by the residual range-dependent phase, which is a fatal problem for high-resolution millimeter-wave (MMW) SAR imaging. In this paper, an extensive investigation on the RCMC accuracy is provided by establishing an accurate formula expression between the range cell migration error and the residual range-dependent phase error. One-step MOCO-based SAR imaging algorithm is investigated by compensating the range-dependent motion error before RCMC, so the presence of range cell migration error would be significantly suppressed. What is more, a modified azimuth match filtering (AMF) function is given by precise topography and aperture-dependent motion compensation (PTA) method to overcome the residual azimuth-dependent phase error in the azimuth compression stage. Both simulated and real-measured MMW SAR data sets are used to validate the analysis for high-resolution airborne SAR imaging.

Wideband Interference Mitigation in High-Resolution Airborne Synthetic Aperture Radar Data

Radio frequency interference is a major issue for synthetic aperture radar (SAR) imaging. Especially with the presence of wideband interference (WBI), the signal-to-interference ratio (SIR) of the measurements is greatly degraded, thus making it difficult to produce a high-quality SAR image. Compared with narrow-band interference (NBI), WBI occupies a larger bandwidth and is more complicated to deal with. This paper addresses the detection and mitigation of WBI in high-resolution airborne SAR data. First, a WBI-corrupted echo is characterized in the time–frequency representation by utilizing the short-time Fourier transform. In this way, the original range-spectrum WBI mitigation problem can be simplified into a series of instantaneous-spectrum NBI mitigation problems. For each instantaneous spectrum, the existence of interference signal can be identified according to the negentropy-based statistical test. Furthermore, the interference signal is mitigated by notch filtering or eigensubspace filtering. The experimental results of the simulated data, as well as real measured data sets, show that the proposed scheme is effective in suppressing the interference signal and in obtaining a high-quality image.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

Waterline Mapping and Change Detection of Tangjiashan Dammed Lake After Wenchuan Earthquake From Multitemporal High-Resolution Airborne SAR Imagery

Several dammed lakes caused by landslides and rock avalanches appeared after Wenchuan earthquake. Tangjiashan dammed lake was the largest one among all of them, which resulted in obvious threats to people around. In this paper, multitemporal high-resolution airborne synthetic aperture radar (SAR) images are used to map the waterline of Tangjiashan dammed lake and its change continuously, which is meaningful for flooding assessment and prediction. An approach combining different techniques is proposed for dammed lake segmentation. In this approach, subpatched intensity thresholding segmentation, morphological operators, and local Gaussian distribution fitting energy (LGDF)-based active contours model (ACM) are used in combination to get the final waterline. Flood-affected area is detected and its size is calculated for each segmental result. In addition, the variations of the flood-affected area are also obtained based on the difference of the above-mentioned segmental results. The proposed approach is tested on real SAR imagery acquired from three different dates in May, 2008 with high-temporal resolution in the same area containing Tangjiashan dammed lake. Experimental results demonstrate the effectiveness of the proposed approach.

Robust river boundaries extraction of dammed lakes in mountain areas after Wenchuan Earthquake from high resolution SAR images combining local connectivity and ACM

River boundaries extraction from SAR imagery is valuable for flood monitoring and damage assessment. Several rivers, parts of which include dammed lakes caused by landslides and rock avalanches triggered by the 2008 Wenchuan Earthquake, were taken as a case study for robust extraction. In this paper, a novel state-of-the-art approach for automated river boundaries extraction using high resolution synthetic aperture radar (SAR) intensity imagery is presented. The key of our approach lies in the combined usage of local connectivity feature of the river and a region-based active contours model (ACM) in a variational level set framework to differentiate between river and the background. First, sub-patched intensity thresholding segmentation is applied to SAR imagery. Pixels with intensities below the threshold are selected as potential river pixels while the others are potential background pixels. Second, potential river pixels are divided into several connected regions, considering that the river is a big connected region, only relatively bigger regions with similar contrast value are retained as the regions of interest (ROI) while others are noise due to pixel-level decision approach in the first step or shadows due to mountains terrain. Third, the ROI and their contours are regarded as local region and the initial contours to refine the river boundaries, which are used to reduce the scene complexity of ACM and its sensitivity to initial situation, respectively. A novel ACM driven by local image fitting (LIF) energy is presented and used for river boundaries extraction for the first time, which is not only robust against inhomogeneity widely spread in SAR imagery but also can work with efficiency without the need of re-initialization during iteration compared to traditional ACM. The proposed approach was tested on numerous high resolution airborne SAR images containing connected rivers or dammed lakes obtained by Chinese domestic radar system after Wenchuan Earthquake. For the overall dataset, the average commission error, omission error and root mean squared error were 6.5%, 3.3%, and 0.51, respectively. The average computational time for 4000 by 4000 image size was 21min using a PC-based MATLAB platform. Our experimental results demonstrate that the proposed approach is robust and effective.

Very-High-Resolution Airborne Synthetic Aperture Radar Imaging: Signal Processing and Applications

During the last decade, synthetic aperture radar (SAR) became an indispensable source of information in Earth observation. This has been possible mainly due to the current trend toward higher spatial resolution and novel imaging modes. A major driver for this development has been and still is the airborne SAR technology, which is usually ahead of the capabilities of spaceborne sensors by several years. Today's airborne sensors are capable of delivering high-quality SAR data with decimeter resolution and allow the development of novel approaches in data analysis and information extraction from SAR. In this paper, a review about the abilities and needs of today's very high-resolution airborne SAR sensors is given, based on and summarizing the longtime experience of the German Aerospace Center (DLR) with airborne SAR technology and its applications. A description of the specific requirements of high-resolution airborne data processing is presented, followed by an extensive overview of emerging applications of high-resolution SAR. In many cases, information extraction from high-resolution airborne SAR imagery has achieved a mature level, turning SAR technology more and more into an operational tool. Such abilities, which are today mostly limited to airborne SAR, might become typical in the next generation of spaceborne SAR missions.

Melt Pond Mapping With High-Resolution SAR: The First View

Melt pond statistics (size and shape) have previously been retrieved from aerial photography and high-resolution visible satellite data. These submeter- or meter-resolution visible data can provide reasonably accurate information on melt ponds, but are greatly constrained by the limited solar illumination and frequent cloud cover in the Arctic region. In this study, we venture into exploring high-resolution synthetic aperture radar (SAR) or imaging radar method for melt pond mapping, which is not severely disrupted by cloud or low solar zenith angle. We analyzed high-resolution airborne SAR images (0.3-m resolution) of midsummer sea ice, acquired from a helicopter-borne SAR system in the northern Chukchi Sea. The pond area and shape (circularity) derived from the airborne SAR images showed that the statistics were comparable to those previously observed from aerial photographs. We argue that high-resolution SAR, together with one-to-one comparison with coincident aerial photographs, can be used to map melt ponds at a level of detail comparable to aerial photography or high-resolution optical satellite remote sensing. Our encouraging results suggest the possibility of using high-resolution SAR (current or future systems) to map melt ponds in the Arctic region.

A Robust Motion Error Estimation Method Based on Raw Data

High-resolution airborne synthetic aperture radar (SAR) systems are very sensible to deviations of the aircraft from the reference track. In high-resolution imagery, the improvement of range resolution increases the difficulty of implementing range cell migration correction (RCMC), while a wider synthetic aperture increases the cumulative time of motion errors which will affect the image quality. To enable accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, due to the limit of accuracy of such systems, motion errors are hard to be compensated correctly, causing mainly the resolution decrease in final image. Moreover, in large swath mode, the range-dependent phase errors are difficult to be compensated by using the conventional autofocus algorithm only. In this paper, we propose a robust motion error estimation method based on raw SAR data. To apply this estimation method, we first estimate the double phase gradients in subaperture. Second, a filtering method based on curve fitting was proposed to reduce the phase estimation errors caused by low signal-to-clutter ratio (SCR). Finally, we propose a weighted total least square method to calculate the motion errors using the filtered phase gradients. Because the proposed algorithm is nonparametric, it can estimate high-order motion errors. This is very important for the airborne SAR, particularly the light aircraft SAR platform, due to their more complicated movement in air turbulence. The versatility that the proposed method can be used in any imaging algorithms is another advantage. The processing of large number of raw SAR data shows that the algorithm is as robust and practical as phase gradient autofocus and can generate better focused images.

Post-earthquake building damage assessment in Yushu using airborne SAR imagery

The synthetic aperture radar (SAR) plays an important role in earthquake emergency response because of its all-time and all-weather imaging capabilities. On April 14, 2010, an MS7.1 earthquake occurred in Yushu county, Qinghai province of China, causing a lot of buildings collapsed. In this paper, the building damage in Yushu city due to the earthquake was assessed quantitatively using high-resolution X-band airborne SAR image. The features of the buildings with different damage levels (collapsed, partial collapsed, non-collapsed) in the SAR image were analyzed first. Based on these building features, we interpreted the individual building damage in Yushu city block by block and got the numbers of the collapsed, partial collapsed and non-collapsed buildings separately for each block, referring to pre-earthquake QuickBird image when necessary. Let the damage index of individual collapsed, partial collapsed, non-collapsed building be 1, 0.5, 0 respectively, the remote sensing damage index of each block was then calculated through remote sensing damage index equation. Finally, the preliminary quantitative relationship between the remote sensing damage index interpreted from the SAR image and that interpreted from the optical image was built up. It can be concluded that a desirable damage assessment result can be derived from high-resolution airborne SAR imagery.