Yunfeng Shao

Double-Channel Bistatic SAR System With Spaceborne Illuminator for 2-D and 3-D SAR Remote Sensing

This paper presents a double-channel hybrid bistatic synthetic aperture radar (SAR) system. It can be implemented with the available illuminator (e.g., spaceborne and airborne SAR systems) to acquire the 2-D and 3-D microwave images for remote-sensing applications. This system can be used as a test system for the validation of complex bistatic acquisitions, novel synchronization algorithms, and advanced imaging techniques. In this paper, we will demonstrate the time and phase synchronization strategies, fast time-domain imaging algorithm, 2-D bistatic SAR, and 3-D bistatic stereo radargrammetry in SAR images. Based on the proposed bistatic system, the acquired bistatic image has a much better sensitivity than its monostatic counterpart, which will facilitate the detection and recognition of targets based on their characteristic and bistatic scattering behaviors. Finally, the experiment results highlight the differences between monotatic and bistatic SAR images.

First Bistatic Demonstration of Digital Beamforming in Elevation With TerraSAR-X as an Illuminator

The next generation of spaceborne synthetic aperture radar (SAR) remote sensing systems will emphasize on high-resolution and wide-coverage imaging. For these design goals, digital beamforming (DBF) in elevation is a promising candidate. DBF-SAR can provide global monitoring capacity for the continuous observation of a highly dynamic and rapidly changing world with high spatial resolution and short repeat intervals. A spaceborne experiment regarding a real complex scene and real spaceborne wave propagation channel effects remains a necessary step to complete the experimental verification of this advanced technique. Fortunately, the spaceborne-stationary bistatic configuration offers a potential chance to validate the advanced technique. The aforementioned experiment can be considered as a test bed for the development and implementation of DBF radar techniques applicable to Earth observation science and planetary measurements. The DBF experiment based on spaceborne-stationary bistatic configuration with TerraSAR-X as an illuminator has been successfully conducted in June 2013 by the Department of Space Microwave Remote Sensing System, Institute of Electronics, Chinese Academy of Sciences.

A New Quality Map for 2-D Phase Unwrapping Based on Gray Level Co-Occurrence Matrix

Both in quality-guide phase unwrapping algorithms and weighted minimum-norm phase unwrapping algorithms, quality maps play a crucial role in obtaining the absolute phase from the wrapped ones. In this letter, a new technique for generating quality maps based on the gray level co-occurrence matrix (GLCM) is proposed. GLCM is a classical second-order statistics method for analyzing the texture features of images. Through exploring the second-order statistics of GLCM, much useful information in the image can be exploited. According to the characteristics of the interferogram, the second-order statistic of GLCM called “difference of entropy” is used to generate the quality maps. Besides, we modified the definition of “difference of entropy” to make the statistic more suitable for the problem. Finally, the new algorithm is compared with other conventional algorithms both in the simulated and real data experiments and the results show its better performance.

Error Analysis of Bistatic SAR Imaging and Stereoscopy Bistatic SAR

The flexible geometry configuration of the bistatic synthetic aperture radar (SAR) has many advantages. However, it causes serious measurement error in the bistatic SAR system, which degrades the quality of the SAR images and the precision of the digital elevation model (DEM) obtained using stereoscopy bistatic SAR. In this paper, the influence of the scene height estimation error, trigger delay, transmitter position measurement error, receiver position measurement error, and transmission line length measurement error are analyzed. These analyses are very useful in bistatic SAR system design. The scene height estimation error, trigger delay, transmitter position measurement error, and synchronization receiver position measurement error affect both the quality of the images and the precision of the DEM obtained by stereoscopy bistatic SAR slightly. The echo receiver position measurement error and transmission line length measurement error affect the quality of the imaging only slightly, but seriously affect the precision of the DEM obtained by stereoscopy bistatic SAR. Luckily, their measurement precision can be quite satisfactory. Simulations and real bistatic experimental results verify the proposed theoretical analysis.

Integrated Denoising and Unwrapping of InSAR Phase Based on Markov Random Fields

In the traditional processing flow of interferometric synthetic aperture radar (SAR) technique, the processing of phase is conducted via two separated and successive steps, i.e., phase denoising and phase unwrapping. That is to say, first, wrapped phases without noise are generated, and then, the true phases without 2π-ambiguities are reconstructed (here and in the rest of this paper, true phase refers to the information-induced unwrapped phase without noise). Such separated steps will inevitably bring in extra estimation error because each step has necessary approximations and presumptions which do not always hold. On the contrary, in this paper, we treat phase denoising and unwrapping as a single problem of true phase recovery from observed ones. Following this methodology, an integrated phase denoising and unwrapping algorithm based upon Markov random fields (MRFs) is proposed. Taking a priori knowledge of interferometric phases into account, MRF is used to model the relationship between the elements in the random variable set including both true phases and their observations. After the model is built up, the energy function of this MRF is defined according to the local-independence property inferred from the MRF structure and then minimized to obtain the estimate of the true phase value. In the end of this paper, experiments on simulated and true phase data are conducted, and the comparison with several commonly used unwrapping methods is proposed to verify the efficiency of the proposed MRF algorithm.

Interferometric Phase Denoising by Pyramid Nonlocal Means Filter

Interferometric phase denoising is a crucial step of interferometric synthetic aperture radar processing flow because it has significant influence on the following steps. Traditional interferometric phase denoising algorithms have a similar drawback that they will wipe off some texture details in phase images while denoising. Nonlocal (NL) means filter, in contrast, can reach a balance between denoising and texture preserving because it utilizes the feature of recursive structures in the whole image. Taking the characteristics of interferometric phase image into consideration, this letter proposes a modified NL means filter algorithm for phase denoising. Moreover, in order to preserve texture to the biggest extent, an iterative algorithm is invented. In the end, experiments on synthetic and real data validate that this algorithm outperforms other traditional denoising methods.

Retrieval of Water Depth of Coastal Wetlands in the Yellow River Delta From ALOS PALSAR Backscattering Coefficients and Interferometry

Coastal wetland ecosystems are among the most productive yet highly threatened systems in the world, and population growth and increasing economic development have resulted in extremely rapid degradation and loss of coastal wetlands. Synthetic aperture radar (SAR) has proved to be of great potential in wetland applications, such as characterizing wetland types and mapping wetland inundation extent, based on the fact that the SAR backscatter signal from the wetland depends mainly on the wetland vegetation and hydrodynamic. However, the absence of ground observations has limited calibration and validation of water depth estimated from satellite SAR data. This letter aims to explore the potential for retrieving the water depth in freshwater marshes using L-band SAR backscattering coefficients. We present an innovative approach for combining backscattering coefficients and interferometric data to estimate water depth from L-band SAR data. The technique was applied to freshwater marshes in the Yellow River Delta using an Advanced Land Observing Satellite Phased Array L-band SAR data set acquired between 2007 and 2010. It is shown that the combination of L-band backscattering coefficients and interferometric data could provide information on the hydrodynamic of the Yellow River Delta with high spatial resolution.

An N 2.5 back-projection algorithm for SAR imaging

In this paper, a modified fast back projection (FBP) algorithm is proposed for Synthetic Aperture Radar (SAR) imaging. The azimuth compression of the proposed FBP is divided into sub-image process and finial image process. The secondary phase correction is used to reduce the error cause by approximation before the finial image process. The interlace sub-image grid method makes image quality uniform for all the pixel in the finial image. The applicability limitations and the sub-image two dimensions over sample method are presented. The computational complexity of the proposed FBP is O(N2.5). Simulation on GPU is given to verify the proposed method efficacious.

Pyramid non-local mean filter for interferometric phase denoising

Interferometric phase denoising is a crucial step of interferometric SAR processing flow. Its performance has great effect on the following steps. Traditional interferometric phase denoising algorithms have a similar drawback that they will wipe off some texture details in the phase image at the same time of filtering noise out. Nonlocal mean filter, in contrast, can find a balance between denoising and texture preserving because it utilizes the recursive structures from the whole image. Taking the features of interferometric phase image into consideration this paper proposes a modified Non-local mean filter algorithm to solve this problem. Moreover, in order to preserve texture to the biggest extend, an iterative algorithm is invented. In the end, experiments on synthetic and real data validate that this algorithm outperforms other traditional denoising methods.

A magnitude weighting process for bistatic SAR digital beamforming implementation

ABSTRACT Digital beamforming (DBF) technology splits the receiving antenna into multiple sub-apertures, which makes a promising candidate for imaging with a wide swath and high gain. Combining bistatic synthetic aperture radar (SAR) configuration with DBF technology provides more flexibility in designing microwave remote sensing missions, and which leads to a new bistatic SAR digital beamforming (BiSAR-DBF) approach. In this paper, a BiSAR-DBF implementation with magnitude weighting process is proposed. The effect of spatially variant heights and the corresponding modification are also analyzed. In the DBF experiment based on spaceborne-stationary bistatic configuration with TerraSAR-X as an illuminator has been successfully conducted in June 2013 by the Department of Space Microwave Remote Sensing System, Institute of Electronics, Chinese Academy of Sciences. Using the proposed method, the signal-to-noise (SNR) of BiSAR imagery is greatly improved.