The all solid-state terahertz (THz) radar has obvious miniaturized integration and high resolution imaging advantages compared with conventional microwave radar. In this paper, a 0.22 THz active frequency-modulated pulse radar system with one transmission channel and four receiving channels is presented, and interferometric inverse synthetic aperture radar (InISAR) imaging experiments, which can acquire altitude information of objects, are carried out. In order to acquire high-quality InISAR images, a calibration method is presented to solve the nonlinearity of wideband signal frequency and phase inconsistency of different receiving channels together. Furthermore, to deal with the phase wrapping in InISAR imaging of objects with large scale, a novel method based on the dominant scatterers to estimate the objects rotation rate is presented. Finally, to show more information of objects in the InISAR images, the imaging results with a large rotation angle by the convolutional back-projection algorithm are obtained. The imaging results verify the superior performance of the multi-channel THz radar system and the imaging processing method, which can provide support for further research on InISAR imaging in the THz band.

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.

In this article, an efficient interpolation‐free algorithm (IFA) applied for cylindrical millimeter‐wave (MMW) holographic three‐dimensional (3‐D) reconstruction is proposed. Compared with previous cylindrical MMW holographic 3‐D reconstruction methods, the proposed IFA can efficiently achieve high‐quality 3‐D reconstruction within the region of interest (ROI). In the IFA, the spherical wave data are decomposed into plane wave components along radial direction and height direction in the wavenumber domain. Then, an angle‐matched filter function containing distance information of the ROI is utilized to reconstruct the corresponding cylindrical coordinate 3‐D imaging result, whose radial maximum projection is then utilized to generate the 3‐D point clouds of target surface. Finally, the 3‐D surface is reconstructed based on the screened Poisson surface reconstruction method. Both simulation and experimental results validate the effectiveness of the proposed method.

Millimeter-wave technology has been widely used in near range targets imaging scenarios, such as mechanical scanning and multiple input multiple output (MIMO) array imaging. Emerging scanning array regimes increase the need for fast-speed and high-quality imaging techniques, which, however, are often subject to specific array positions. Moreover, the relationship between array positions and the imaging performance is not clear, which leads to no uniform standard for array design. In this paper, a series of array configurations are designed to explore the impact of different array positions on the cross-range imaging performance. Meanwhile, a novel fast fully focused imaging algorithm with wavenumber domain properties is presented, which is not constrained by the positions of the transmitters and receivers. Simulation and experimental results show that, compared with a conventional algorithm, the proposed algorithm has a faster imaging speed under the same imagining quality. This study provides a feasible method for fast fully focused imaging in the case of location-constrained MIMO arrays, or partially damaged transceivers.

In this article, a modified complex‐valued convolutional neural network (MCV‐CNN) specifically for interferometric inverse synthetic aperture radar (InISAR) imaging is proposed. Comparing with the fast Fourier transformation‐based and sparsity‐driven imaging algorithms, the MCV‐CNN can achieve super‐resolution and side‐lobe suppression on the imaging results simultaneously within a short time. The inputs of the MCV‐CNN are complex‐valued radar echo data, and the outputs are complex‐valued ISAR images which contain both the amplitude and phase information. Then the phase information is adopted to perform an interferometric operation, and the high‐quality three‐dimensional InISAR imaging results can be achieved. A 0.22 THz InISAR imaging experiment has been carried out to show the superiority of the proposed method on imaging quality and computational efficiency.

No abstract

Motion compensation is a crucial step to inverse synthetic aperture radar imaging, and envelope correction is the foundation of motion compensation. Research on envelope correction based on the small-angle imaging model has matured after years of development. However, the small-angle imaging model is not applicable to parameter estimation and imaging of micro-motion targets. According to the characteristics of the micro-motion targets and the superiorities of terahertz imaging radar, an envelope correction method for micro-motion targets in the terahertz region was proposed in this paper, including the jump error correction based on periodic correction and drift error compensation based on nonlinear fitting. Then a 330 GHz imaging radar and two experiments on corner reflectors and a warhead model were introduced. The validity of the method was verified by the experimental results, and the performance of the method was proved by the inverse Radon transform of the range profile sequences.

Vibration induces a micro-Doppler effect, which contains crucial motion information and features of the micro-motion target. However, the traditional radar can only acquire micro-motion information in the radial direction. The multi-channel radar is capable of acquiring actual micro-motion information in a three-dimensional space, including amplitude, frequency, and three-dimensional direction of vibration. Moreover, the high-accuracy parameter estimation can be achieved in the terahertz band. In this paper, a method for three-dimensional micro-motion feature exaction and parameter estimation is proposed, including a phase-derived-range algorithm, interference, and auto-correlation. Meanwhile, to prove feasibility of the method, the results of simulations and experiment based on a 0.22 THz multi-channel radar system are presented after theoretical analyses.