Yabo Liu

Ground Moving Target Extraction in a Multichannel Wide-Area Surveillance SAR/GMTI System via the Relaxed PCP

This letter presents a novel approach for extracting moving targets in a multichannel wide-area surveillance radar system. In the algorithm, after proper preprocessing and matrix combination, the combined matrix of radar echoes can be regarded as the superposition of three matrices, namely, a low-rank matrix of ground clutter, a sparse matrix of moving targets, and an entry-wise matrix of noise component. Then, the recently proposed relaxed version of principal component pursuit is used to realize ground clutter (low-rank matrix) and moving target (sparse matrix) separation under the influence of entry-wise noise. Both simulation and real data processing results are provided to demonstrate the effectiveness of the proposed method. In addition, the results show the advantage of the proposed method in a nonhomogeneous environment when compared with a reduced-dimension space-time adaptive processing method.

Achieving High-Quality Three-Dimensional InISAR Imageries of Maneuvering Target via Super-Resolution ISAR Imaging by Exploiting Sparseness

Interferometric inverse synthetic aperture radar (InISAR) can achieve 3-D imageries of maneuvering target. However, the quality of 3-D imageries suffers from the noise and sidelobes seriously. In addition, the defocusing effect due to the nonlinear moving of the target can also bring into a bad effect for 3-D imaging. To tackle these issues, a 3-D InISAR imaging approach via compressed sensing (CS)-based super-resolution (SR) ISAR imageries is proposed. First, we establish the target sparsity-constraint optimization model containing both amplitude and phase information of scatterers. Second, a Bayesian CS approach is adopted to get high-quality SR ISAR image. The quasi-Newton solver guarantees both high amplitude and phase information recovery precision. At last, a high-quality 3-D view of the target is achieved via the conventional ISAR imagery pair interferometry technique. Computer simulation and real data experimental results verify the effectiveness of the proposed method.

Sharpness-Based Autofocusing for Stripmap SAR Using an Adaptive-Order Polynomial Model

A novel autofocusing technique is developed for image from stripmap-mode synthetic aperture radar (SAR) data. The approach is based on maximizing the image sharpness function that induces the solution to maximum-posterior estimation. In this letter, closed-form expressions are derived for the gradients of the sharpness function with respect to the coefficients of the polynomial expansion, which makes the use of conjugate gradient algorithm available. Additionally, we also design a modified adaptive-order searching strategy, and it helps to remarkably reduce the computational load while maintaining the accuracy. Real airborne SAR data experiments and comparisons demonstrate the validity and effectiveness of the proposed algorithm.

High-Quality 3-D InISAR Imaging of Maneuvering Target Based on a Combined Processing Approach

In order to enhance the target recognition probability in the inverse synthetic aperture radar (ISAR) imaging domain, the interferometric ISAR (InISAR) mode is presented to achieve the 3-D information of a target. However, the real data results of a maneuvering target are not enough, due to the difficult signal processing. In this letter, a combined processing approach is proposed to realize high-quality 3-D imagery of a maneuvering target. In the approach, the range alignment and phase adjustment are implemented together on echoes to avoid destroying the coherence of the echoes. Then, the high-quality 3-D InISAR imagery of the maneuvering target can be reached. Real data results are provided to confirm the effectiveness of the proposal.

Polarimetric Response of Landslides at X-Band Following the Wenchuan Earthquake

A fully polarimetric response of landslide areas at X-band was studied by a Chinese high-resolution airborne synthetic aperture radar system. Polarimetric decompositions, including the Yamaguchi four-component decomposition and the Cloude decomposition, are used to analyze the scattering mechanisms of several typical landslides caused by the 2008 Wenchuan Earthquake in southwestern China. The experimental results indicate that areas affected by large-scale landslides show complicated scattering mechanisms at X-band, which are a mixture of surface, double bounce, and volume scattering. Simple classification results based on supervised Wishart classifier and polarimetric scattering similarity parameters are also presented, which can distinguish landslide areas from others, such as forest and water, very well. However, it does not perform well for urban areas. Additional information, such as prelandslide imagery, is needed to distinguish landslide areas from urban areas or bare soil. From these results, we can conclude that landslide mapping using fully polarimetric data has great potential for rapid response and management of landslide disasters.

Improved Full-Aperture ScanSAR Imaging Algorithm Based on Aperture Interpolation

In this letter, an improved full-aperture imaging algorithm for scanning synthetic aperture radar (ScanSAR) mode is proposed, which fills the data gaps between bursts through a linear-prediction-model-based aperture interpolation technique in a subaperture manner before azimuth compression. It can significantly suppress the spikes induced by periodical data gaps and, at the same time, enhance the signal-to-noise ratio of the obtained ScanSAR imagery. This approach has a great potential in the interferometric context. The effectiveness of the proposed approach is demonstrated by both simulated and real ScanSAR data with different types of terrain. All the experimental data were acquired by the C-band SAR system with a bandwidth of 200 MHz, which was developed by the Department of Space Microwave Remote Sensing System, Institute of Electronics, Chinese Academy of Sciences.

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.

Extension and Evaluation of PGA in ScanSAR Mode using Full-Aperture Approach

In order to enable a testbed for spaceborne scanning synthetic aperture radar (ScanSAR) mode, in this letter, a ScanSAR autofocusing approach for airborne platforms has been developed. Autofocusing algorithms, such as the phase gradient autofocus (PGA) algorithm, prove to be a useful postprocessing technique to get refocused synthetic aperture radar images. However, conventional stripmap PGA does not work in ScanSAR mode when the full-aperture approach is used, due to the periodic data gaps in each subswath. To solve this problem, we extend the stripmap PGA to ScanSAR with some modifications, mainly in the subaperture segmentation and phase error estimation steps. The performance of extended stripmap PGA is evaluated by an airborne ScanSAR data set containing different types of terrain, with a high spatial resolution up to 3.5 m in azimuth.

Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space

Abstract A simple and effective approach for unsupervised classification of large-scale landslides caused by the Wenchuan earthquake is developed. The data sets used were obtained by a high-resolution fully polarimetric airborne synthetic aperture radar system working at X-band. In the proposed approach, Pauli decomposition false-color RGB imagery is first transformed to the hue-saturation-intensity (HSI) color space. Then, a good combination of k-means clustering and HSI imagery in different channels is used stage-by-stage for automatic landslides extraction. Two typical case studies are presented to evaluate the feasibility of the proposed scheme. Our approach is an important contribution to the rapid assessment of landslide hazards.

Autofocus Correction of Residual RCM for VHR SAR Sensors With Light-Small Aircraft

Due to the light weight and small size, synthetic aperture radar (SAR) sensors with light-small aircraft are very sensitive to atmospheric turbulences, which cause serious trajectory deviations. Limited by the cost or payloads, light-small aircraft sometimes cannot carry high-accuracy inertial navigation systems (INS)/global positioning systems (GPS). For the very high resolution (VHR) case, residual range cell migration (RCM) often exceeds several range resolution cells during the course of the synthetic aperture, thus degrading the image quality substantially. In this paper, a robust scheme for the correction of residual RCM is presented. The scheme consists of three principle steps. First, the range-compressed data in the signal domain are divided into subapertures in azimuth. For each subaperture, a sliding window is used to select the subblock data with the highest signal-to-clutter ratio. Second, for each subaperture, residual RCM is estimated by using the selected subblock data based on a nonparametric entropy minimization technique. Third, the estimated residual RCM of all subapertures are filtered and coherently combined to perform the correction for the full-aperture data. Processing the results of VHR SAR raw data shows that the proposed scheme is effective for highly precise imaging with light-small aircraft equipped with only low-accuracy INS/GPS.