Ruliang Yang

A New Superresolution SAR Imaging Algorithm based on Extrapolation

In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.

A three-dimensional imaging algorithm for tomography SAR

The three-dimensional image quality of tomography SAR is limited by the non-uniform track distribution in repeat-pass data acquisition. In order to overcome the drawbacks of known methods caused by the non-uniform track distribution, a new three-dimensional imaging approach is proposed based on backprojection for tomography SAR in this paper. Raw data of tomography SAR in X-band is simulated and three-dimensional image is achieved. The imaging result is analyzed, and simulation results confirm the validity of the proposed method.

Investigation on Tree Height Retrieval with Polarimetric SAR Interferometry

Polarimetric SAR interferometry (POLInSAR) has been widely applied in tree height retrieval. A refined algorithm of three-stage inversion process for polarimetric SAR interferometry is proposed in this paper. The refined algorithm focuses on resolving the ambiguity estimation of the volume coherence. The coherence region extraction algorithm is combined with the three stage inversion algorithm to obtain accurate estimate of volume decorrelation. According to the physical explanation of the scattering model of the forest area, we can conclude that the proposed algorithm can get more accurate inversion results. The proposed algorithm is applied to simulated coherent L-Band SAR data provided by ESA, and the validity of the modified algorithm is confirmed.

A novel nonparametric method of ground moving target indication based on bi-channel SAR-ATI

The paper proposes a nonparametric method for ground moving-target indication (GMTI) using along-track interferometric synthetic aperture radar (SAR), which does not require the theoretical derivations of the joint probability density function of the interferometric magnitude and phase for both homogeneous and heterogeneous clutter. In the proposed approach, a best-fit curve is set as the detection threshold to separate moving targets from clutter and noise. A special technique, termed sliding-window technique, is then employed to reduce residual clutter and noise. The validity of the method has been demonstrated by the experiments performed on simulated spaceborne SAR data.

SAR target recognition based on sub-block statistical features extracted from the Gabor filtered image

A method for SAR target recognition using low-frequency sub-band and Gabor filter sub-block statistical feature is proposed. The sub-band image extracted from the pre-processed SAR image is filtered by Gabor filter on different directions and scales. The each filtered sub-band image is divided into different sub-blocks and the statistical features derived from every sub-block of all filtered sub-band images are regarded as the target recognition feature, which can be used to recognize the targets with SVM. The proposed method is validated on MSTAR dataset for 3-type SAR target recognition.

Multi-polarization SAR characteristics analysis based on the raw data simulation

The method of multi-polarization SAR characteristics analysis based on the raw data simulation is presented in this paper. This method includes the theory of the simulation of multi-polarization raw data and the technique of SAR system analysis. The models of the point target and the distributed target are applied to the simulation which concentrates on SAR system parameters and focus on the backscattering model, so as to understand SAR characteristics completely. At the end of this paper, some examples performed aim to validate the effectiveness of the method of the polarization simulation and help us to understand the SAR multi-polarization characteristics.

Stepped-Chirp Burst Waveform and SAR Imaging

The stepped-frequency signal is a kind of flexible high-range resolution waveform, it is sensitive to the radial velocity, and the couple between range and Doppler is very complicated. The target energy is distributed to the adjacent range cells, which results in the degradation of the range resolution and the loss of SNR.

Super-Resolution Imaging Method Based on Regularization and Deconvolution

The process of radar-radiating electromagnetic waves and receiving the backscatter echo signal can be expressed in the form of matrix operations. The backscattering RCS of the remote sensing region can be estimated by matrix inversion method.

The Basis of Microwave Imaging Radar

Synthetic aperture radar (SAR) obtains the two-dimensional high-resolution image by means of pulse compression technology in range dimension and synthetic aperture processing in azimuth dimension.

SAR Super-Resolution Imaging Method Based on Spectral Estimation

Super-resolution information processing technology of synthetic aperture radar uses super-resolution imaging algorithms, namely the use of high-resolution spectral estimation methods to alternate Fourier spectrum estimation method, the extrapolation of efficient signal spectrum or the adaptive weighting methods.