In this article, a novel low-cost frequency scanning-based synthetic aperture radar (F-SAR) system is proposed for high-resolution imaging. F-SAR scheme is demonstrated for personal screening for the first time. A hybrid scanning model is presented to illuminate the human body, namely, frequency control beam steering in cross-track and mechanical scanning in along-track. A frequency scanning-based tomographic SAR focusing algorithm is proposed. Accordingly, a power spectrum estimation algorithm in cross-track and synthetical aperture processing in along-track are compounded in the signal processing framework. Unlike a variety of multiple input multiple output (MIMO) array imaging which illuminates the object by switching different channels sequentially over separate time intervals, the F-SAR concept sweeps across all swaths over each chirp by employing a frequency scanned beam. Herein imaging time and hardware cost can be significantly cut down by dimensionality reduction from the MIMO system to a single input single output (SISO) system. Furthermore, to fulfill the particular scheme of the F-SAR system, a novel combo antenna module, leaky-wave slotted waveguide combined with a cylindrical lens, is proposed and achieved at 78–92-GHz band, by which a steering fan-beam focused at the object under test (OUT) plane is radiated. The radiation beam is focalized by the cylindrical lens accompanied by frequency sweeping, while is diffused in along-track. The frequency-controlled beam-steering concept and the fan-beam focusing mechanism are verified by the chamber measurements. The measured scanning range is 23°. Beamwidth of 11–16 mm is obtained at the focal plane. Beam steering in cross-track together with mechanical scanning in along-track can attain a field of view (FoV) of 0.54 2 $\text{m}^{2}$ . Through-clothes imaging of person-borne concealed objects and the real-time capability are demonstrated by experiments. Resolutions in both along-track and cross-track can reach 5 mm.

The automatic extraction of the targets which we are interested from a given image is the fundamental of the automatic detection and identification for security screening systems based on imaging technologies. Suffering from the comparatively low signal to noise ratio (SNR), the automatic detection of targets in a passive Terahertz (THz) imaging system facing great challenges, but in urgent necessary. In this paper, a comprehensive method for automatic detection of concealed targets in passive THz image by making the best use of the ‘block statistics uniformity’ properties of the passive images is firstly studied. A theoretical model for the ‘featured regions’ decomposition based on the minimization of a ‘fit energy’ functional with respect to a ‘surface function’ is established, to overcome the drawbacks of conventional methods with gradient-based edge operators for their unsuccessful application in low SNR passive images with blurred boundaries. Based on above theoretical basis and taking advantages of the distinguished contrasts of the convergent ‘surface function’ in different ‘featured regions’, an automatic detection algorithm with three steps was further developed to automatically extract the number, the locations and the shapes of all the concealed targets, with the shape of each target derived as the contour point series arranged in clockwise direction. With plenty of experimental results in 0.2THz band, it's found that, the proposed method has high detection accuracy about 95% with quite good real-time performance, even for the single channel proof-of-state system with low SNR. The theorem, algorithm and results in this paper may have important applications in unmanned and intelligent security screening systems without any artificial interventions.

In this study, a quasi‐real‐time human respiration detection method with prominent signal‐to‐noise‐and‐clutter ratio (SNCR) improvement is proposed to increase performance of ultra‐wideband rescue radar under the low SNCR conditions such as through‐wall or other similar conditions. Three main steps of the proposed method are designed for the purpose of effectively removing stationary clutter, suppressing non‐stationary interference from other moving subject and improving the contrast between respiration response and clutter. Meanwhile, the proposed method satisfies the requirement of quasi‐real time as its time cost implemented in MATLAB is only 2 s. Experiments are carried out in through‐wall/floors/artificial‐ruin conditions, and results show that the proposed method outperforms the previously proposed method, and it can be a good choice for human respiration detection in complex scenarios due to the prominent SNCR improvement.

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.

Millimeter-wave (MMW) holographic imaging technology is widely used in plenty of short-range applications like security and medical diagnosis. When combining with multiple-input-multiple-output (MIMO) array, such a technology can acquire precise reconstruction with wider field of view and higher dynamic range. However, to focus the higher dimensional data set obtained from MIMO architecture, the complicated iteration or interpolation employed by the previous state-of-the-art focusing techniques prevents the real-time operation of such an imaging system under a general computation power. It is more economical to increase the operational speed by improving the algorithm efficiency. Hence, a novel fast imaging algorithm that uses multistatic frequency scaling technique is proposed in this article for achieving real-time 3-D imaging on a 1-D MIMO scanning system. Only fast Fourier transform (FFT)/inverse FFT (IFFT) and multiplications are employed in the algorithm, which can be easily implemented. Compared with the previous state-of-the-art techniques, the proposed algorithm has the lower computation complexity. Practical experiments with self-developed MMW MIMO scanning radar prove the accuracy and efficiency of the algorithm. On a common laptop without any acceleration technology, the proposed algorithm requires less than one tenth of the time as required by the previous state-of-the-art techniques.

The characteristics of the range cell migration (RCM) under single-input-multiple-output (SIMO) bi-static geometry are studied and an omega-K algorithm for near-field 3-D imaging based on planar SIMO or multiple-input-multiple-output (MIMO) array is proposed. The RCM and the linear part of the range offset (RO) within SIMO data are corrected by employing a 3-D Stolt transformation. The residual range error is further compensated by phase multiplication and an image-domain interpolation. Reconstruction for a MIMO aperture can be achieved by adding together all the focusing results from its SIMO subarrays. The implementation details of the algorithm are described. The imaging resolution and the sampling requirements for a MIMO aperture are discussed. Since the RO correction is achieved by an approximate way, the spatial limitation for accurate reconstruction is also given. The imaging accuracy and the high efficiency of the algorithm are demonstrated both by simulations and experiments with various distributed targets based on planar MIMO arrays. Real-time 3-D imaging for planar SIMO/MIMO aperture is expected to be achieved by using the algorithm.