As a widely used communication signal, orthogonal frequency division multiplexing (OFDM) signal has good sensing performance. It is the key technology of the integration of sensing and communication (ISAC), which is the potential core technology of the sixth generation mobile communication. The fusion of Multiple input and multiple output (MIMO) technology and OFDM signal was conducted to improve the communication speed and imaging resolution of ISAC system. In our work, the multi-signal classification (MUSIC) algorithm is adopted to process MIMO-OFDM data and achieve time of arrival (TOA) and direction of arrival (DOA) estimation. Based on the simulations and experiments in a variety of multi-object scenes, it shows that the MUSIC algorithm can restore the position of the objects more accurately and more robustness than traditional ways.

In this paper, an azimuth velocity estimation method based on spectral peak measurement-moving target shadow detection (SPM-SD) is proposed. Compared with the existing methods, this method takes into account the effect of the moving target position on the doppler shift and improves the accuracy of the azimuth velocity estimation value. The doppler modulation frequency of the azimuth phase is then estimated by using the fractional Fourier transform (FrFt), which in combination with the azimuth velocity gives an estimation of the distance velocity of the moving target. Finally, the estimation results are used to construct the first-order and second-order phase compensation functions for azimuth phase compensation, and the phase gradient autofocus algorithm (PGA) is used to compensate for the residual quadratic and higher phase errors. The real CSAR data processing results prove the effectiveness of the proposed method and greatly improve the imaging quality of the moving target.

High precision and high efficiency motion error compensation is a very challenging work for Terahertz synthetic aperture radar (THz-SAR) imaging, the tiny vibration of platform will make seriously THz-SAR image defocused. In this paper, a new compensation method based on the division of range sub-band conjugate, name as SBCM, is presented for THz-SAR effective motion correction. In the scheme, we use image entropy to iterate the overlap rate of the divided range sub-bands of THz-SAR echoes, and conjugate multiplying the division range-compressed results to obtain a more ideal imaging effectively. Both simulation and experiment results demonstrate the effectiveness of SBCM method. Compared with traditional echo-derived phase estimated autofocusing method, SBCM method not require parameter estimation and its arithmetic is small.

This paper introduces a method based on sub-aperture division for estimating the cross-track velocity of moving targets in terahertz circular synthetic aperture radar (CSAR). By carefully choosing the number of sub-apertures, the complete aperture is divided into multiple smaller apertures. In the sub-aperture regime, the small-angle approximation is applied to separate the cross-track velocity from other parameters related to moving targets. This approach allows for precise estimation of the cross-track velocity, facilitating accurate repositioning of the moving target. The effectiveness of the proposed method is confirmed through experimental results, evidencing its practicality.

This letter addresses the problem of changes in target shape and structure during imaging caused by different height structures being focused at the same height in the terahertz (THz) band. A new circular synthetic aperture radar (SAR) imaging algorithm based on the extraction of target structure scattering characteristics is proposed to solve this phenomenon. First, a circular SAR (CSAR) imaging model is established for different heights. The target was imaged at different heights, resulting in a series of image sequences in different height and azimuth directions. Then, incoherent tracking of the backscattered energy is used to search for effective scattering centers at different heights. The scattering characteristics curves of different structures are obtained based on the effective scattering centers. Finally, the effectiveness of the proposed algorithm is verified by simulation and measured data. The proposed algorithm has accurately focused the target, while also enhancing the details. In addition, the contrast-to-noise ratio of the imaging results has been improved by 4.87% compared to traditional algorithms.

A terahertz (THz) airborne synthetic aperture radar (SAR) with a carrier frequency of up to 220 GHz is developed. However, due to the short wavelength of THz, the motion compensation (MOCO) algorithm suitable for submeter resolution SAR systems becomes ineffective. To address this issue, we propose an extended Kaiser distribution optimization (EKDO)-based phase compensation algorithm for airborne THz SAR imaging. First, a subaperture division strategy is employed to divide the full-aperture data into multiple subapertures. The envelope error and phase error are roughly compensated using the combination of inertial measurement unit (IMU) and global positioning system (GPS) data. Then, the linear error of the compensated echo is estimated using the Doppler centroid estimation. Subsequently, the EKDO MOCO algorithm proposed in this article is used to compensate for the quadratic phase error. In the third step, residual errors are compensated using a high-order phase error estimation (HPEE). Finally, real data from experiments conducted in four different types of scenarios all confirmed the effectiveness and validity of the algorithm.

Terahertz (THz) circular synthetic aperture radar (CSAR) demands higher precision in motion compensation (MOCO), posing significant challenges. To address this issue, this article proposes a multichannel MOCO algorithm based on adaptive subaperture division (MCAAD). First, the adaptive aperture division (AAD) algorithm is used to divide the image into multiple subapertures. Within each subaperture, initial coarse compensation is performed using data recorded by the inertial navigation system (GPS/INS). Subsequently, high-frequency vibration errors are compensated using the interferometric phase of different channels. Then, an image reconstruction algorithm is employed to image the compensated results, and a residual error estimation (REE) algorithm is applied to compensate for high-order phase errors and residual envelope errors, yielding well-focused subaperture images. Finally, the subaperture images are fused using a base-4 registration algorithm. The simulation and experimental results with measured data demonstrate that the proposed algorithm effectively compensates for THz CSAR imaging.

Synthetic aperture radar (SAR) human-imaging technology has been widely used in the fields of security screening and activity recognition. However, most of the existing methods aim at stationary human targets, resulting in severe restrictions on their potential applications. In this article, an SAR imaging method for walking human is proposed with short aperture terahertz (THz) radar. This method is based on a modified wavenumber domain approximate algorithm ($\text{m}{\omega }$ka), whose interpolation mapping is modified according to the approximation of region of interest (RoI). Because the nonrigid motion phase error caused by the walking human would lead to severe deformation and blur in imaging results, a compensation processing is essential. To figure it out, the fractional Fourier transform combined with the maximum and minimum generalized likelihood ratio test (FrFT-mmGLRT) is devised in this article. Within a short aperture time, the nonrigid motion of walking human can be approximately assumed as a superposition of the rigid movements of different human body parts. Particularly, by taking advantage of the superposition property of FrFT, the motion phase errors of different human body parts are distinguished and estimated by jointly searching for the peaks of FrFT energy spectrum. Furthermore, the mmGLRT-based composite imaging technique is utilized to obtain a whole body result from the compensated results of different body parts. Finally, numerical simulation and real experiments are conducted to verify the feasibility and capability of the proposed method for walking human SAR imaging.

This paper proposes an imaging algorithm with adaptive aperture energy division. This method is suitable for circular synthetic aperture radar (CSAR). The algorithm is an extension of the traditional CSAR polar format algorithm (PFA). Firstly, to avoid the loss of image detail information caused by the mismatch between the aperture size and the energy distribution in the traditional self-aperture division, a method based on the aperture energy to divide the sub-aperture is proposed. Then, according to the PFA algorithm image the sub-apertures separately, and perform incoherent fusion of the imaging results to quickly obtain high-resolution imaging results. Finally, simulation results validate the feasibility of the proposed approach.

With multi-sensor-based collision avoidance systems (CASs) being adopted in today’s automobiles, a new method that enables collaborative decision-making with preceding vehicle detection under various external environments is needed. In this paper, spatial–temporal correlations of multi-channel signals that are collected by multiple sensors on the host vehicle are considered, and a multi-channel detection technique with a stochastic model is introduced for automobile collision avoidance. We propose an accurate and robust multi-channel, generalized likelihood ratio test (GLRT)-based detection and collaborative decision-making scheme, with a vehicle kinematic analysis for avoiding rear-end collisions. The results of simulations and physical experiments demonstrated that our detector expands the detection range with a high detection rate and that our proposed scheme obtains good performance under varying operating and environmental conditions.

We propose a fast algorithm to circular synthetic aperture radar (CSAR) imaging for arbitrary region of interest (ROI). This algorithm is an extension of traditional CSAR polar format algorithm (PFA). Firstly, to avoid severe defocus and distortion of off-centered ROI image caused by traditional CSAR PFA plane-wave approximation error, a novel PFA matched filter kernel is derived with ROI characteristic reference function. Then, according to the wavenumber support domain approximation of ROI, a new interpolation mapping relation is defined to obtain uniform rectilinear wavenumber domain data from polar format echo data. With the rectilinear data, the imaging result of ROI can be obtained by two dimensional inverse fast Fourier transform.

Due to the merit of low cost and flexible flight, small drones are showing tremendous application prospect in both military and civil fields. Aiming at public area monitoring, a synthetic aperture radar (SAR) imaging model using drone fleet borne radars is proposed. In this model, the radars illuminate the imaging area while the drones fly forward straightly. To make the implementation easier, we assume that each radar transmits signal and receives echo independently. Furthermore, the frequency-division (FD) signals are adopted for different radars to avoid interference. With broadband signal, synthetic aperture via the motion of the drones and linear array formed by the multiple radars, three-dimensional (3D) imaging can be realized. Numerical simulations are conducted to verify the effectiveness of the proposed model and the 3D image formation method.

The performance of vehicle detection system is often affected by both internal and external noise. In this paper, a novel vehicle detection scheme called vehicle detector based on EMD-HT and multichannel GLRT (V-EHMG) is proposed, which composed of signal denoising part based on empirical mode decomposition (EMD) and signal detection part which takes advantage of the spatial–temporal relationship acquired by multiple sensors. In the first part, we propose a new denoising algorithm null-hypothesis interval threshold EMD denoising (EMD-HT) to check the similarity between the probability density function of the decomposed intrinsic mode functions (IMFs) from input signal and the generalized Gaussian distribution to determine relevant IMFs for signal reconstruction. Combined the interval threshold method, the denoised signals are acquired. In the second part, we use multichannel generalized likelihood ratio test (GLRT) detector to judge the presence of other vehicles with the denoised signals as the input. Simulation and physical experimental results show that with V-EHMG, the signal-to-noise ratio of the signal is doubled and the detection range is improved more than 40% compared with the traditional methods.

Video synthetic aperture radar (ViSAR) is a novel imaging model to persistently surveil the region of interest by a series of consecutive images in real time. The formation time of one frame image, which can influence the image latency, is one of the key factors to realize ViSAR system. In general, the polar format algorithm (PFA) is preferred for ViSAR imaging. However, the 2-D resampling in the PFA has a large computation burden and is complex to realize in the real-time processing system. It has become the main obstacle to reduce image latency. Therefore, we derive four judgment criteria in this letter. According to these criteria, we propose the improved method of the PFA. Based on this method, the modified PFA can reduce the image formation time while guaranteeing the image quality. Simulation results are presented to validate the effectiveness of the improved method proposed in this letter.

ABSTRACT The signal of a hypersonic spacecraft entering the Earth's atmosphere may be lost at a certain altitude transitorily. This phenomenon is called “blackout,” an important performance feature of aircraft design. Recently, with the development of the nearcraft, communication techniques under the plasma environment have increasingly become more important, with the realization that we can record, monitor, track, and capture the nearcraft. In this paper, an idea based on the capability of radiation from the terahertz communication system to penetrate the plasma sheath is proposed to provide the theoretical basis for real‐time communication with the nearcraft. Copyright © 2012 John Wiley & Sons, Ltd.