Since there is no atmospheric influence, space-based terahertz inverse synthetic aperture radar (THz-ISAR) can obtain high-resolution images of space targets at a certain distance, so it has important application prospects. In addition, the relative motion of space-based platforms and space targets is complicated. For some satellites that are tumbling out of control or are undergoing attitude change, the imaging angle formed by the target relative to the radar can be considered to be non-uniform, which in turn leads to imaging defocus.In this paper, a minimum entropy-based THz-ISAR rotation parameter estimation and motion compensation method for nonuniformly rotating space targets is proposed. Firstly, the radar echo is compensated for the translational motion and corrected for the range migration to obtain an envelope-aligned one-dimensional range profile. Then, the minimum entropy (ME) algorithm based on Newton’s method (NM) is used to estimate rotational velocity and centre of the targets, and to compensate the range second-order spatial-variant (SV) phase. After that, the golden section method is applied to estimate the target rotational acceleration and compensate the azimuth second-order spatial-variant phase. Finally, the cyclic variable method is used to iterate these two compensation steps alternately to avoid the coupling effect of range and azimuth second-order spatial-variant phase, while obtaining the target rotation parameters and the well-focused imaging results.
In the study of spatial target component recognition based on terahertz radar imaging using the traditional YOLOv5network, the recognition performance of the model decreases due to large overlapping areas of components in some samples and unclear imaging of small components. To address this issue, this paper proposes a typical component target recognition model, BoT-YOLO+, based on an improved YOLOv5 network architecture. On one hand, the proposed model enhances performance by introducing the BoTNet backbone architecture, which incorporates the attention mechanism from Transformers and improves the feature extraction capability for small components and thereby increasing the recognition rate of small components, without significantly increasing computational costs.
Terahertz frequency is high, and which is suitable for the realization of large signal bandwidth. At the same time, terahertz wave has benign anti-stealth and anti-interference ability. Terahertz radar can obtain the fine scattering characteristic information of the target, which is of important significance for target fine detection, target recognition and terminal guidance. However, because of the huge difference between the size of targets and the wavelength in the terahertz, the scattered near-field region of the target is up to tens of kilometers in distance. Therefore, In the terahertz band, most of the scattering targets are located in the near-field region. When the terahertz radar detects the target, the electromagnetic scattering should not be similar to the plane wave, and therefore the far-field radar scattering cross-sectional area theory is no longer applicable. It is absolutely vital to analyze the near-field electromagnetic scattering characteristics of the terahertz band. This report mainly carries out simulation analysis, and which calculation method is the Large element Physical Optics method. Firstly, the variation of the RCS of the standard target sphere and plate in the terahertz band with the distance is calculated and analyzed in the near-field. When it degenerates to the far-field, the calculation result satisfies the analytical solution of the standard target RCS, which verifies the correctness of the calculation method. Secondly, to analyze the RCS of the complex aircraft scale target in the terahertz band throughout 360°, and drawn the RCS distribution of the rectangular coordinate system and the polar coordinate system.
The challenge of forward-looking imaging has persisted in the field of radar remote sensing. Owing to the unique imaging geometry, the commonly employed synthetic aperture radar (SAR) cannot synthesize a wide effective aperture for targets in front of the radar. In this paper, we introduce a novel imaging method that eliminates the need for relative motion between the radar and the target to tackle this issue. This method falls under the category of phase-front-modulation-based imaging technologies. Firstly, an azimuthal phase front control technique utilizing a uniform linear array (ULA) is introduced. This approach enables the generation of antenna beams with linearly varying phases. Secondly, the radar response is constructed from multi-time measurements using different modulated beams. An imaging model is established, and a target reconstruction method based on the fast Fourier transform (FFT) is proposed. Subsequently, the proposed method is validated via simulations, and its resolution capabilities are assessed. Finally, the autoregressive (AR) model is employed to extrapolate the radar response, achieving superresolution imaging outcomes. The work can benefit the development of novel information-rich radar based on phase front modulation.
KEYWORDS: Detection and tracking algorithms, Reconstruction algorithms, Radar, Stereoscopy, 3D image processing, 3D acquisition, Image restoration, Radar imaging, 3D modeling, Tin
High-resolution near-field three-dimensional (3D) radar imaging techniques with millimeter and terahertz wave have played an increasingly significant role in applications including hidden object detection and nondestructive testing. Currently, imaging methods suffer from low efficiency when imaging defects in stratified media. This is caused by the inadaptability of the fast Fourier transform in the frequency domain due to the alteration of wave numbers in different media. We propose an imaging method based on the nonuniform fast Fourier transform to overcome the problem. Numerical simulations and experiments were carried out to verify our idea. Results show that our proposed method can greatly improve the imaging efficiency while maintaining the imaging quality. This work is of great significance for future development of nondestructive testing technology based on millimeter wave/terahertz imaging.
In recent years, cylindrical millimeter-wave (MMW) holographic imaging technique has attracted a lot of attention for its special advantages, including high resolution, large aperture, and strong penetrability. A modified wavenumber-domain three-dimensional imaging algorithm applied for near-field cylindrical MMW holography is proposed. The core of the proposed algorithm is to generate an accurate and efficient phase compensation factor in wavenumber-domain. Compared with the existing algorithms, the proposed algorithm holds advantages in both imaging speed and imaging quality and is more suitable for security inspection application. Both the simulation results of point targets and the experimental results of the resolution test panel validate the effectiveness of the proposed algorithm.
Attribute scattering centers model (ASCM) can provide important geometric information regarding the illuminated target. However, sliding scattering center (SSC) cannot be well extracted based on the current ASCM. This paper proposes an efficient method to extract SSCs based on density-distance (DD) matching. First, the scattering characteristic of SSC is derived theoretically from the perspective of physical optical (PO). Then, the frequency dependence and estimated position are analyzed by the multi-peak model. The distance and density of each scattering center are constructed and cluster by the proposed DD -based matching algorithm. Finally, the geometrical structure corresponding to each scattering centers can be retrieved. Simulation results validate the feasibility and accuracy of the proposed method.
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