Dahai Dai

The Interferometry Phase of InSAR Coherent Jamming with Arbitrary Waveform Modulation

This paper focuses on the interferometry phase of an active coherent jamming in InSAR (Interferometry Synthetic Aperture Radar) images. Based on the signal models of coherent jammer, the jammings imaging results are derived by employing the Omega-K algorithm. By comparing the imaging results of InSARs two channels, the jammings interferometry phases for both working modes, the single-pass and repeat-pass modes, are proved to be constants. And the values of the interferometry phases are determined by the jammers geometry position relative to InSAR baseline, but independent of the jammings waveform modulation and its background terrain.

THE "SLOPE" EFFECT OF COHERENT TRANSPONDER IN INSAR DEM

Although a Coherent Transponder (CT) is widely utilized in the field of Synthetic Aperture Radar (SAR), its Digital Elevation Model (DEM) has not yet been well studied for Interferometry SAR (InSAR). Based on the fact that the interferometry phase is a constant for CT with single transmit antenna, this paper mainly focuses on InSAR DEM induced by CT. The decorrelation effect in the intersection region of CT and natural terrain is researched in detail to support the analysis of CT’s phase-unwrapping. The most important property, which makes DEM of CT unique, is found to be the “slope” effect. The incline angle of “main slope” of DEM is verified to be determined only by the depression angle of InSAR baseline, whereas the incline angles of the “subordinate slopes” are affected by all the geometric parameters of InSAR baseline. Finally, all the incline angles are independent of CT’s waveform modulations, since the modulations have no contribution to the interferometry phase.

Three-Dimensional Reconstruction of Man-Made Objects Using Polarimetric Tomographic SAR

The growing interest in 3-D reconstruction of targets, particularly man-made objects, has made synthetic aperture radar (SAR) tomography a hot topic in recent years. It obtains a 3-D reflectivity map by coherently processing multiple images acquired from slightly different views. This paper investigates the use of polarimetric tomographic SAR to reconstruct 3-D images of man-made objects and proposes a polarimetric 3-D reconstruction technique, based on the multiple-measurement vector compressive sensing (CS) (MMV-CS) model and Tikhonov regularization theory. The main feature of the technique is that of allowing joint reconstruction of polarimetric 3-D reflectivity maps with high resolution. For X-band tomographic SAR, we demonstrate that the phase error induced by an array element error is severe enough to prevent data focusing and propose a phase calibration technique employing prominent scatterers to adapt the proposed technique to practice. To check the plausibility of our algorithms, a ground-based SAR system is introduced, and high-resolution 3-D images obtained by processing the real collected data are presented. As special cases of the new proposed technique, both the Tikhonov regularization and the MMV-CS method reconstruct the targets successfully and give an accurate estimate for the vehicle size. Compared to the Tikhonov regularization method, the MMV-CS technique exhibits much better superresolution power and lower sidelobe level. The advantage of the MMV-CS technique over the single-measurement vector CS technique is also demonstrated, and the phase calibration algorithm is verified.

Instantaneous polarization statistics of electromagnetic waves

The problem of statistical description of instantaneous polarization of electromagnetic waves is studied. First, the physical meanings of instantaneous Stokes vectors’ components are analyzed, which provide a short cut for solving statistical distribution functions of instantaneous Stokes vectors. Second, in the condition of Gaussian hypothesis, the analytical expressions of probability density function (PDF) of instantaneous Stokes vectors are presented. Finally, some computation results are presented in the condition of two independent polarization channels, which show the validity and simplicity of the statistical description method.

IMAGING ENHANCEMENT OF STEPPED FREQUENCY RADAR USING THE SPARSE RECONSTRUCTION TECHNIQUE

Based on the observation that sparsity assumption is well satisfled in the synthetic aperture radar (SAR) imaging applications, there is increasing interest in utilizing compressive sensing (CS) in SAR imaging. However, there are still several problems which should be concerned in CS-based imaging approaches. Firstly, inevitable noise and clutter challenge the performance of CS algorithms. Secondly, the super-resolving ability of CS algorithms is not su-ciently exploited in most cases. Thirdly, nonideal characteristics of mutual coherence afiect the performance of CS algorithms in complex scenes. In this paper, a novel CS imaging framework is proposed for the purpose of improving the imaging performance of stepped frequency SAR. Meanwhile, a super-resolving imaging algorithm is proposed based on the nonquadratic optimization technique. Simulated and rail SAR measured data are applied to demonstrate the efiectiveness of the novel framework with the proposed super-resolving algorithm. Experimental results validate the superiority of this method over previous approaches in terms of robustness in low SNR, better super-resolving ability and improved imaging performance in complex scenes.

Comment on "Orientation Angle Preserving A Posteriori Polarimetric SAR Calibration"

This paper is comment on “Orientation Angle Preserving A Posteriori Polarimetric SAR Calibration”.

Grid-based probability density matrix for multi-sensor data fusion

The multi-sensor multi-target localization and data fusion problem is discussed, and a novel data fusion method called grid-based probability density matrix (GBPDM) is proposed. Dividing the common observe space into numerous of small grids, the measurements containing uncertainties can be represented by their sampled probability density functions. By adding probability density of all measurements taken from one sensor grid by grid, we got the probability density matrix (PDM) of this sensor. Combining PDMs of all sensors together produce a joint PDM. Peaks in the joint PDM can be considered as estimated locations of targets. Theoretic analysis show that the computation cost is proportional to the product of the number of sensors and that of targets, and will not lead to combinatorial explosion. The presented method has a high precision and is suit for parallel processing. Simulation results verify the feasibility and validity of the proposed technique.

Superresolution Polarimetric ISAR Imaging Based on 2D CP-GTD Model

This paper presented a new approach to superresolution ISAR imaging based on a scattering model called coherent polarized geometrical theory of diffraction (CP-GTD) which is better matched to the physical scattering mechanism. The algorithm is a joint processing between polarization and superresolution essentially. It can also estimate the number, position, frequency dependence, span, and normalized scattering matrix of scattering centers instantaneously for each channel rather than the one which extracts parameters from each channel separately, and its performance is better than the latter because the fully polarized information is used. The superiority of the CP-GTD is verified by experiment results based on simulated and real data.

Clustering-Based Geometrical Structure Retrieval of Man-Made Target in SAR Images

In synthetic aperture radar (SAR) images, scattering centers (SCs) from the same geometric structure of the man-made target usually have the same scattering type and similar coordinates. Inspired by this observation, a novel clustering-based geometrical structure retrieval (C-GSR) method is proposed to estimate the geometrical structure of targets by clustering SCs according to their types and coordinates. The C-GSR method considers each peak in a SAR image as a single SC and extracts both frequency and polarization features for classification. Then, SCs are efficiently clustered using the density-distance-based clustering algorithm. Finally, the geometrical structure corresponding to each canonical scatterer can be retrieved by computing the coordinates of SCs associated with the corresponding cluster. Experimental results have demonstrated the feasibility and accuracy of the proposed C-GSR method.

Polarimetric 3D reconstruction of manmade objects

A new polarimetric tomography technique based on compressive sensing is proposed in this paper for the applications such as 3D reconstruction of man made target. Compared to the existing methods, the advantages of this new technique are those of preserving full image resolution, no model order selection procedure, high resolution, and low sidelobe artifacts. The effectiveness of the technique is demonstrated by processing real data collected by ground rail SAR.