To predict the propagation of radio waves in the environment of dielectric ground and dielectric obstacles, a new two-way parabolic equation (2W-PE) method based on the domain decomposition principle and surface impedance boundary conditions (SIBC) is proposed. First, we decompose the obstacle area into different subdomains and derive the SIBC in each subdomain in detail; then, the discrete hybrid Fourier transform (DMFT) in the upper subdomain and finite difference (FD) algorithm in the lower subdomain is used to solve 2W-PE combined with SIBC, respectively. After that, we explain the algorithm steps in the process of calculating the total field, compared with the traditional 2W-PE, and then finally introduce the method of moments (MoM) combined with the enhanced discrete complex image (E-DCIM) method for accuracy verification of the new 2W-PE algorithm. The simulation results show that no matter how the obstacle medium parameters change, the results of 2W-PE method proposed in this paper and MoM are always in good agreement, which proves the accuracy of 2W-PE and its superiority in speed. Therefore, this paper provides a reliable and efficient method for solving the problem of radio wave propagation in the presence of obstacles, especially in the case of low-lossy obstacles.

As a non-iterative linear inverse scattering imaging method, the linear sampling method (LSM) has the merits of easy implementation and high computational efficiency. In this article, based on the LSM and T-matrix method, we propose a fast method to reconstruct the target medium parameters. First, we use the LSM qualitative imaging method to estimate the contour of the target. Then, the preprocessing information of the LSM is applied to the virtual experiment circles in the framework of T-matrix method. In this way, we avoid the inversion of the matrix and only need to solve a series of univariate equations. Numerical simulation results show that the reconstruction accuracy of the proposed method is similar to that of LSM quantitative imaging method, but it has higher calculation accuracy and wider application range. Although the calculation accuracy is not as good as the contrast source inversion (CSI) method, the proposed method has huge advantages in terms of calculation efficiency.

To study the problem of radio wave propagation in an environment of dielectric ground and obstacles, especially in low‐lossy obstacles, to consider the propagation inside the obstacle, a new method is proposed to solve the two‐way parabolic equation based on the principle of domain decomposition. First, a mathematical model of parabolic equations for reflection and refraction in an environment with obstacles is established. Then, the area of the obstacle is decomposed into two different subdomains; the discrete mixed Fourier transform is used to calculate the field value in the upper subdomain from the top of the obstacle to the absorption boundary, the finite difference method is used to calculate the field value of the lower subdomain inside the obstacle, and the field strengths and phases of the two subdomains coordinate with the boundary conditions. In the process of calculation, we emphatically consider the multiple reflection and transmission paths inside obstacles to make the algorithm results more accurate. In addition, we verified the stability and convergence of the method. Finally, the simulation results show that the proposed method and the method of moments have good consistency, so the algorithm has the characteristics of strong applicability and fast calculation speed, which provide a novel and reliable method to research the wave propagation problem in a modified environment of obstacles.

An improved two‐way parabolic equation (2WPE) method for predicting radio wave propagation in obstacle environment is proposed. Classical 2WPE is mainly utilised for calculating radio propagation under irregular terrain by taking the undulating ground and obstacles as a whole, which yields calculation precision is very limited by the terrain inclination. In order to address the above problems, according to the principle of domain decomposition, by dividing the obstacles and the ground into different zones, 2WPE can be improved to calculate the fields in obstacle environment. With the improved 2WPE, the real phases of both the forward and backward waves can be retrieved when a radio wave entering and leaving the obstacles, and the total field can be obtained by superposition of forward and backward waves. After that, method of moments (MoM) is applied to verify the accuracy of the improved 2WPE in the short distance. In the simulation, the equivalent source model is used to unify the initial field or source settings of 2WPE and MoM to improve the verification precision. The accuracy and superiority of the improved 2WPE are proved, which lays a foundation for the analysis of radio wave propagation in the more complex environment.

A two-way parabolic equation (2W-PE) method based on machine learning is proposed to predict the spatial field strength of radio waves propagating over undulating terrain. The method first performs longitudinal domain decomposition on a step distance, and uses different algorithms to solve the 2W-PE in each subdomain. Then a simple obstacle model (SOM) containing three stepping units of different heights is introduced. A variety of undulating terrains can be approximated using the overlay combinations and lateral extensions of multiple SOMs, and combined with machine learning method, the boundary condition coefficients in different environments can be determined. The simulation results show that the proposed 2W-PE method is in good agreement with the method of moments (MoM), which verifies its accuracy and superiority.

In this paper, an improved T-matrix method is proposed to improve the accuracy for simultaneous reconstruction of dielectric scatterers and perfectly electric conductors (PEC). First, we modify the original T-matrix inversion method and obtain a preliminary reconstruction result. Then treat this result as a priori information, and a new initial iteration value is generated by truncating and assigning values to it. At the same time, genetic algorithm (GA) is used to optimize these truncation and assignment parameters. Finally, the optimization result is used as the initial value of the modified T-matrix method to obtain better reconstruction accuracy. The numerical simulation results under noisy conditions show that the proposed method can more clearly reconstruct the edges of the objects and have higher reconstruction accuracy.