Micro-motion characteristics of conical-shaped high-speed moving targets are presented using the Lorentz finite-difference time domain (Lorentz-FDTD) method. This research discusses the transformation formulas of the space and time increments, the incident wave, the field components between the moving system, and the laboratory system in case of a micro-motion target. The validity and accuracy of the proposed transformation formulas are verified by presenting results for a moving cone and a hemisphere-cylinder combination target.

Composite materials are widely applied in aerospace, civil engineering, and sports equipment. Various damages produced during fabrication and long-term use can destroy its original mechanical properties, which brings safety and structural healthy concerns. Microwave imaging based on time reversal (TR) is one of the most promising nondestructive testing methods for portable, low-cost, and accurate testing with the advantages of auto-focus and super-resolution. This paper applied microwave TR for the detection of buried small damage in composites backed by metal plates. Strong reflection from composite–metal interfaces brings challenges in successfully achieving time-reversal auto-focusing on small and weak-scattering damages in composites. Traditional target localization methods, including the entropy regularization method and time-integrated energy method, may result in the wrong localization of small damages. The main contribution of this paper is that the localization problem caused by the strong reflection from metal plates is revealed first, and the target initial reflection method from through-wall-radar imaging is introduced to solve it. The performance of three target localization methods is investigated, and the physical reasons for failure or successful localization are discussed in detail. Some performance influence factors, such as the arrangement of receivers or the total time step of received signals, are also discussed. Good performance for the detection of a single small damage with a weak scattered signal is achieved, and the performance for detecting multiple damages is studied. All time-reversal simulations are carried out based on the finite-difference time-domain method.

Microwave time reversal (MTR) as a microwave imaging method can provide auto-focus and super-resolution with real-time, efficient, high contrast, and low cost properties. It is applied here for non-destructive testing (NDT) of small defect buried in multi-layer composites backed by metal. It is critical to estimate the focusing time with localization methods in MTR. The traditional entropy regularization method (ERM) may give a wrong focusing time estimation for the strong reflection from background metal. This leads to a wrong localization of defect. An improved ERM (IERM) is proposed here by properly combining ERM and target initial reflection method (TIRM) to ensure a correct localization. MTR based on IERM (IERM-MTR) is then applied to detect the defect in multi-layer composites when the permittivities of each layer are known. Its stability, accuracy, and noise tolerance are proved by multiple numerical investigations. An iterative strategy based on IERM-MTR and particle swarm optimization (PSO) method is also proposed here for detecting the defect in multi-layer composites when the permittivities of each layer are unknown. Numerical investigations are carried out to prove its effectiveness. Small defects are easily detected in multi-layer composites applied here.

The stability and convergence performance of Levenberg–Marquardt method for acousto-electric tomography (AET) applied to different levels of conductivity contrast is studied in this paper. As a multi-physical imaging modality, acousto-electric tomography (AET) provides high spatial imaging resolution while also conserving the high contrast property of electrical impedance tomography. The Levenberg–Marquardt method is a well known iteration scheme which can be applied for the nonlinear problem of AET. However, the influence of the conductivity contrast on the stability and convergence performances of this conductivity reconstruction method is rarely discussed in the literature. In this paper, the performance of the Tikhonov regularization-based Levenberg–Marquardt method is applied to reconstruct conductivity map with different conductivity contrast between different regions of the domain of interest (DOI). Numerical investigations are carried out for phantoms with different conductivity contrast. Reconstructed results with different levels of noise are presented and discussed in detail.

An improved entropy regularization method has been proposed in a previous work of the authors in two-dimensional (2D) for overcoming a wrong localization problem while the imaging method based on microwave time reversal is used for detecting the defects in multilayer composites backed by metal. This method is further investigated in this paper for defect detection in three-dimensional (3D) objects composed of multilayer composites. Its effectiveness for solving the wrong localization problem in 3D is validated in particular via detecting a small defect in a multilayer composite skin of an aircraft wing model. Its performance and noise tolerance on 3D imaging of small defects is first studied based on a planar composites, and the influence of source polarization is also discussed in detail. Afterwards, 3D imaging of small defects in a four-layer glass-fiber-reinforced composite skin for an aircraft wing model is carried out. Different levels of noise are applied to the time-reversed signals. 3D imaging results are discussed in detail. The effectiveness and stability of the proposed improved entropy regularization method for 3D non-destructive testing of defects in multilayer composites are finally validated.

Small defect detection in thin-walled structures is a difficult problem in non-destructive testing, particularly these in aircraft skin. This paper proposes a novel method based on the time reversal of guided microwave for detecting small buried defects in composite skin of aircraft wing flap. The generation mechanism of guided microwave is revealed, and the guided microwaves carrying information of small defects can propagate along the composite skin without attenuation. Then, the guided microwaves are collected by receivers and processed with microwave time reversal. Numerical results indicate that the proposed method can achieve super resolution detection for multiple small defects, even with noisy signals. The effectiveness and noise tolerance of this method are validated through two-dimensional and three-dimensional aircraft wing flap models covered by composite skin.