Jingkun Gao

Efficient Terahertz Wide-Angle NUFFT-Based Inverse Synthetic Aperture Imaging Considering Spherical Wavefront

An efficient wide-angle inverse synthetic aperture imaging method considering the spherical wavefront effects and suitable for the terahertz band is presented. Firstly, the echo signal model under spherical wave assumption is established, and the detailed wavefront curvature compensation method accelerated by 1D fast Fourier transform (FFT) is discussed. Then, to speed up the reconstruction procedure, the fast Gaussian gridding (FGG)-based nonuniform FFT (NUFFT) is employed to focus the image. Finally, proof-of-principle experiments are carried out and the results are compared with the ones obtained by the convolution back-projection (CBP) algorithm. The results demonstrate the effectiveness and the efficiency of the presented method. This imaging method can be directly used in the field of nondestructive detection and can also be used to provide a solution for the calculation of the far-field RCSs (Radar Cross Section) of targets in the terahertz regime.

Experimental 0.2THz radar system for RCS measurement

A terahertz (THz) radar system with the highest frequency up to 0.22THz is described in this paper. The system is built based on the microwave up-conversion technology and with a good performance in operating range. The radar cross section (RCS) measurement of different objects, namely, corner reflector, cylinder, rectangular plate and a scale car model, is performed based on the THz system. By the comparison of the measurement results of the rectangular plates with different surface characterization, a conclusion is reached that the detailed surface has a considerable influence on RCS values. Moreover, the RCS values of the car model with different incident angles are obtained based on the measurement experiments.

A Novel Method for 3-D Millimeter-Wave Holographic Reconstruction Based on Frequency Interferometry Techniques

A novel interferometry technique is proposed and introduced into active millimeter-wave (MMW) holography. Different from optical holographic interferometry, which relies on a reference light source or the interferometric synthetic aperture radar where data from apertures of different elevations are interfered, data are interfered between different frequencies in the proposed method. Higher ranging accuracy is achieved, since the residual phase information which is always neglected is utilized by the interferometry manner. The proposed method also avoids interpolations in the traditional MMW holographic imaging algorithms, by which the computational complexity can be reduced. First, theoretical derivation of the 3-D reconstruction method based on frequency interferometry is presented, and detailed algorithms considering noise resistance and phase unwrapping are designed. Then, numerical simulations are conducted to validate our methods. Different aspects of the proposed algorithms’ performance are analyzed and compared with previous methods. Finally, laboratory experiments are carried out. Both the simulation and experimental results validate the superiority of our method on reconstruction accuracy and computational efficiency.

Near-Field Three-Dimensional Planar Millimeter-Wave Holographic Imaging by Using Frequency Scaling Algorithm

In this paper, a fast three-dimensional (3-D) frequency scaling algorithm (FSA) with large depth of focus is presented for near-field planar millimeter-wave (MMW) holographic imaging. Considering the cross-range range coupling term which is neglected in the conventional range migration algorithm (RMA), we propose an algorithm performing the range cell migration correction for de-chirped signals without interpolation by using a 3-D frequency scaling operation. First, to deal with the cross-range range coupling term, a 3-D frequency scaling operator is derived to eliminate the space variation of range cell migration. Then, a range migration correction factor is performed to compensate for the residual range cell migration. Finally, the imaging results are obtained by matched filtering in the cross-range direction. Compared with the conventional RMA, the proposed algorithm is comparable in accuracy but more efficient by using only chirp multiplications and fast Fourier transforms (FFTs). The algorithm has been tested with satisfying results by both simulation and experiment.

Electromagnetic Scattering Characteristics of Rough PEC Targets in the Terahertz Regime

To deal with the perfect electric conductor rough targets’ scattering problem, which is the basic premise of the radar applications at terahertz frequencies, a hierarchical semideterministic modeling and full-wave-algorithm-based computation method was proposed. The scattering fields with phase information and synthetic aperture images of electrically large cubes with different surface characteristics were obtained. The influence of the surface roughness can be easily observed. According to the imaging results, we can predict that other than the scattering calculation challenges caused by the surface roughness, it also brings great benefits that more detailed information about the targets will emerge on the images.

A Three-Dimensional Surface Imaging Method Using THz Dual-Frequency Interferometry

A novel 3-D surface imaging method based on terahertz (THz) dual-frequency interferometry is proposed for the detection and imaging of metal objects. The interferometer is formed first in the range direction with two azimuth-elevation images at different THz frequencies. Then, the 3-D surface image can be obtained by interference processing of two azimuth-elevation imaging results. Compared with the traditional wideband 3-D imaging, the proposed method can avoid the nonlinear error caused by the signal nonlinearity. In addition, the image registration for the interference processing is evitable, when the frequency difference satisfies certain conditions. Based on the electromagnetic calculation data, the 3-D surface imaging results of both rough cone and rough cube validate the effectiveness of the proposed method. Furthermore, the reconstruction error increases slightly with the increasing of the error of frequency difference, which indicates that the proposed method has a good tolerance with respect to frequency instability.

Multiple-views real array imaging for terahertz radar

In this work a multiple-views real array imaging method for terahertz radar is demonstrated and theoretically explained based on synthetic aperture technique. Taking full advantage of short wavelength of terahertz wave, the real transreceiver array can provide high-resolution in transverse dimensions, while a wideband signal provides the resolution in the range dimension. Based on the inverse synthetic aperture radar imaging principle, an improving of transverse resolution is realized by acquirement of multiple virtual apertures. Several individual, coherent images of a target, which are resulted from the relative rotation between the transreceiver array and targets, are simply superposed to create a high-resolution image. Simulations by electromagnetic calculation data verify the proposed imaging scheme.

Range-azimuth SAR imaging based on Bayesian Compressive Sensing

In this paper we develop an efficient anti-noise imaging algorithm based on Bayesian Compressive Sensing (BCS) theory. Random sampling is applied in range and azimuth direction respectively, and sparse dictionary matrixes are designed independently in each direction according to imaging geometry model. At last, BCS theory is used to reconstruct SAR image. BCS theory takes the prior knowledge of targets into consideration as well as the additional Gaussian noise, and therefore it can reconstruct images more clearly and robustly. The computer experiments show that the imaging algorithm developed in this paper performs better in anti-noise ability and spatial resolution compared to FFT-based algorithms and the orthogonal matching pursuit (OMP) algorithm. Thus we can obtain higher image resolution. When compared to the algorithms where only one sparse dictionary is designed for two-dimension area, this algorithm has much lower computational complexity and needs less memory.