Developing Realistic FDTD GPR Antenna Surrogates by Means of Particle Swarm Optimization
نویسندگان
چکیده
The antenna is the most important part of a ground-penetrating radar (GPR) system and defines employed electromagnetic pulse how it transferred to ground. It crucial account for these coupling effects in numerical simulations implement realistic models, e.g., full-waveform inversion (FWI). We present method developing adapting 3-D finite-difference time-domain (FDTD) models GPR antennas, complete with electric components, dielectric material properties, feed details. exemplify this commercially available, shielded 400 MHz antenna, model which was set up by fitting synthetic data an experimental signal reflected at metal plate air. For FWI, we used particle swarm optimization (PSO) algorithm because fit parameters show complex individual on waveform. resulting then validated against measured air, water, near field antenna. Overall, reproduce validation very accurately. Signals objects placed change shape frequency content radiated wavelet varying subsurface properties are emulated correctly.
منابع مشابه
Design of the Compact Ultra-Wideband (UWB) Antenna Bandwidth Optimization Using Particle Swarm Optimization Algorithm
In this paper a particle swarm optimization (PSO) algorithm is presented to design a compact stepped triangle shape antenna in order to obtain the proper UWB bandwidth as defined by FCC. By changing the various cavity dimensions of the antenna, data to develop PSO program in MATLAB is achieved. The results obtained from the PSO algorithm are applied to the antenna design to fine-tune the bandwi...
متن کاملAntenna Diversity using Particle Swarm Optimization
Particle swarm optimization technique is a soft computing approach and has many Engineering applications. In this paper the optimization technique viz., Particle swarm optimization is used to calculate separation between antennas. Space diversity method is based upon the principle of using two or more antennas in order to receive uncorrelated radio signal. By doing this, there is a possibility ...
متن کاملDeveloping Niching Algorithms in Particle Swarm Optimization
Niching as an important technique for multimodal optimization has been used widely in the Evolutionary Computation research community. This chapter aims to provide a survey of some recent efforts in developing stateof-the-art PSO niching algorithms. The chapter first discusses some common issues and difficulties faced when using niching methods, then describe several existing PSO niching algori...
متن کاملNon-linear stochastic inversion of regional Bouguer anomalies by means of Particle Swarm Optimization: Application to the Zagros Mountains
Estimating the lateral depth variations of the Earth’s crust from gravity data is a non-linear ill-posed problem. The ill-posedness of the problem is due to the presence of noise in the data, and also the non-uniqueness of the problem. Particle Swarm Optimization (PSO) is a stochastic population-based optimizer, originally inspired by the social behavior of fish schools and bird flocks. PSO is ...
متن کاملThinning of antenna array via adaptive memetic particle swarm optimization
Massive multiple input multiple output antenna array is crucial for the fifth generation wireless communication. Proper antenna array design can reduce interference among different signals and generate desirable beamforming. Sparse antenna array is able to form narrower beam with lower sidelobe than equally spaced antenna array given the same number of array elements. However, determining the p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Antennas and Propagation
سال: 2022
ISSN: ['1558-2221', '0018-926X']
DOI: https://doi.org/10.1109/tap.2022.3142335