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In this study, a novel coarse-to-fine image registration algorithm based on feature matching using the Gabor filters is provided for repeat-pass SAR interferometry (InSAR). In the coarse registration, we propose a feature-based algorithm developed using the Gabor odd filter ratio-based operator (GOFRO), and the innovative feature based on the GOFRO (GOFRO-F) consists of the improved nonlinear scale space and the descriptor. The establishment of nonlinear scale spaces informed by the GOFRO enhances the stability of feature detection. Also, an improved 64-dimensional descriptor based on the GOFRO is presented to optimize the capability of feature matching. In the fine registration, we employ the normalized correlation coefficient algorithm (NCCA) and the random consensus sample (RANSAC) for determining offsets and the sub-pixel projection model calculation. The datasets of interferograms are derived from the 0.3 THz stepped-frequency radar. Compared to other algorithms, registration experiments of both simple and complex scatters show that GOFRO-F is more suitable for high precision image registration because of its enhanced robustness to the speckle noise. Furthermore, the three-dimensional (3D) reconstruction is conducted based on our proposed algorithm. The results demonstrate that our proposed algorithm facilitates the attainment of millimeter-level spatial resolutions for InSAR in THz band (THz InSAR).

In this paper we introduce an end-to-end deep learning (DL) framework for magnetic anomaly detection (MAD) and denoising. This framework consists of two neural networks: a binary classification network for magnetic anomaly detection and a regression network for geomagnetic noise suppression. The two networks work in a cascade mode: the magnetic field measurement is first sent to the detection network to check the existence of the anomaly signal, and then to the denoising network for extracting the signal from the geomagnetic noise if the detection result is positive. The core idea of our proposed method is that the characteristics of both the magnetic anomaly signal and the geomagnetic noise can be learned from massive training data. The experimental results show that: (1) under the same false alarm rate constraint, the probability of detection of our proposed method is above 80% when the signal-to-noise ratio (SNR) equals -6 dB, while the orthogonal basis function (OBF) method fails when the SNR is below 0 dB; (2) for geomagnetic noise suppression, an improvement of 10 to 15 dB is achieved for data with input SNRs between -5 and 15 dB. Our results paved the way for data-driven magnetic anomaly detection and denoising.

In this paper, the enhanced phase shift migration (PSM) algorithm for multi-input-multi-output (MIMO) side-looking (SL) scheme was proposed for the 2-dimension (2D) fast image reconstruction in the terahertz (THz) band. By decomposing the MIMO imaging problem into a superposition of several single-input-multiple-output (SIMO) sub-arrays, the proposed algorithm can be applied to systems with randomly distributed transmitting array. By deriving and applying the modified phase shift factor and necessary phase compensation, zero-padding in the transmitting array and data reorganization in the spatial-frequency domain of the conventional wavenumber domain MIMO algorithm can be totally avoided, which will hopefully further reduce the amount of calculation. A comprehensive MIMO-SL-EPSM algorithm was established in the wavenumber domain. Proof-of-principle experiments in the 0.1-THz band were performed based on a MIMO-SL prototype system. The reconstructed images for different targets with high efficiency and quality demonstrate the theoretical results and the effectiveness of the proposed algorithm.

An arc-shaped distributed multilayer capacitive loading structure combined with resistive loading is presented in this paper to enhance the radiation performance of folded bowtie antenna (FBA). The radiation efficiency of the loaded bowtie antenna (BA) is improved, and the low-frequency bandwidth is broadened by the bent loop circuits. Additionally, a novel technique of cavity groove is proposed to design the reflector. The optimized cavity tightly coupling with the radiation part overcomes the shortcomings of conventional cavity-backed BAs. The improved ultra-wideband (UWB) FBA with low profile is then designed and fabricated. The basic geometry of the proposed antenna is combined by a novel acorn-shaped bent bowtie patch and a hollowed stepped back cavity. The simulated -10 dB impedance bandwidth of the proposed antenna is over 100 MHz-1100 MHz while the measured operating bandwidth is 250 MHz-850 MHz. This BA of folded type obtains a high realized gain of 4 dBi at 850 MHz and a narrow pattern over the whole band. Time-domain measurements and field tests for practical ground-penetrating radar (GPR) applications have been carried out and the results demonstrate the advanced performance.

In this paper, the extended phase shift migration (PSM) for three-dimensional (3-D) multi-input-multi-output synthetic aperture radar (MIMO-SAR) imaging in terahertz (THz) band was studied. Based on one-dimensional MIMO arrays combined with synthetic aperture scan along another dimension, MIMO-SAR imaging scheme allows the number of array elements to be greatly reduced compared with the two-dimensional (2-D) MIMO arrays. By analyzing the derived analytical expression of the scattered waves in the frequency-wavenumber domain, the MIMO-SAR data in a certain frequency is mapped to another frequency of the `explode fields' of the monostatic form in accordance with a newly defined 3-D dispersion relations. By multiplying the modified phase shift terms in each frequency of `explode fields', the `explode fields' at different range planes can be reconstructed. Finally, the `explode fields' at time t = 0 can be successfully derived to realize fast imaging reconstruction for MIMO-SAR, with great reduction on the time consuming as compared with the BP algorithm and better accuracy compared with the Stolt migration. Additionally, due to its iterative nature in the range direction, the proposed algorithm is more flexible in treating more complicated scenarios, such as the image reconstruction in the multi-layer medium. A bistatic prototype imager was designed for the proof-of-principle experiments in THz band. The 3-D imaging results of different targets and computational complexity were also given to demonstrate the good performance of the proposed algorithm for THz MIMO-SAR imaging.

Dielectric lenses are widely used in terahertz imaging and communication systems to focus or collimate the Gaussian beam by adjusting the phase distribution of wave front. However, due to the high frequency and short wavelength of the terahertz band, the focusing lenses used in the application systems are usually electrically large, which bring the extremely difficulty to carry out efficient electromagnetic (EM) simulation and optimization design. In this paper, a dimensionality reduction concept was introduced to achieve efficient design and optimization of electrically-large terahertz lenses, which have symmetric structures and are commonly used in quasi-optical systems, such as circular lenses and cylindrical lenses. To precisely solve the EM problem with reduced dimension, a two-dimensional moment method (2D-MOM) for homogeneous dielectric targets was studied and successfully developed by solving the surface coupled integral equation discretized with appropriate basis and test functions. Then, the dimensionality reduction approach with the combination of the ray-tracing method (RTM) and the 2D-MOM was developed for the shaped design of terahertz lens with high efficiency. A 0.3THz lens with diameter 10cm was designed with the proposed approach as an example, with its pattern measured by a terahertz field scanning platform. It's found that, with the dimensional reduction, the unknowns can be reduced more than 1500 times and the memory required can be reduced more than 2.5 million times, as compared to the traditional 3D-MOM simulation. And the simulation results agree well with the experiments, which both demonstrate the greatly improved performance of the lens designed by the proposed approach, as compared to the standard lens.

Semi-airborne electromagnetic method (SAEM) is a geophysical electromagnetic detection method which places the transmitting subsystem on the ground and the receiver subsystem on the flight platform. This transceiver configuration has been found to be more efficient than that of the traditional ground electromagnetic methods while it can get much deeper penetration than the traditional airborne electromagnetic methods. Therefore, the SAEM has been widely used in mineral, groundwater, geothermal, and other resources exploration fields. In this paper, we would like to take the most key problems encountered in the SAEM system design and application as the starting point, and then we focus mainly on reviewing the progress of the transmitter, sensor, and receiver technology, as well as data processing, modeling, and imaging methods of the SAEM in China. In particular, the research progress of multi-source SAEMs will be introduced. Beyond that, two prospecting examples with different SAEM systems will be introduced. Finally, we will discuss the future of the SAEM in terms of equipment developing, data processing, modeling and inversion, to promote the research and application in this field to a higher level.

This paper considers the detection and localization of a human subject in complex environments using an ultra-wideband impulse radar. The subject is remotely sensed by extracting micro-motion information, such as the respiration and heartbeat frequencies. It is challenging to extract this information due to the low signal to noise and clutter ratio in typical disaster environments. To improve the localization accuracy, a new method is proposed using the characteristics of vital sign signals. The range is determined using a short-time Fourier transform of the kurtosis and standard deviation of the received signals. Furthermore, an improved arctangent demodulation technique is used to determine the frequency of human micro-motion based on a multiple frequency accumulation method. Performance results are presented, which show that the proposed method is superior to several well-known techniques.