Affiliation:
1. College of Mathematics and Computer Science, Yichun University , Yichun 336000 China
Abstract
Abstract
The electromagnetic scattering characteristics of foam in Marine environment are studied in this paper. The Elfouhaily sea spectrum model is established, and the dielectric constants of seawater/ocean foam are calculated based on the double Debye dielectric constant model, furthermore, the formula relation between them is given. As an important factor affecting ocean electromagnetic scattering, the thickness of foam is proportional to the wind speed above the sea surface. In this paper, the SMCG method based on the surface current equation is mainly used to calculate the electromagnetic scattering coefficient of the environment, and the correctness of the SMCG algorithm is verified by comparing the calculated results with the actual measured data. Based on the computer simulation, the influence of the existence of ocean foam on the environmental scattering is discussed, and the Marine electromagnetic scattering coefficients under different wind speeds, different scrape angles and different radar bands are calculated. Through the analysis of the calculation results, the influences of wind speed, grazing angle and frequency on the electromagnetic scattering characteristics of the Marine environment containing foam are studied, and the general variation rule is obtained: the intensity of electromagnetic scattering increases with the increase of wind speed, the decrease of incident Angle and the increase of frequency. The results of this paper can be used to guide ocean navigation and fishery, and have reference significance in the military field.
Subject
Electrical and Electronic Engineering
Reference22 articles.
1. C. Oliver and S. Quegan, Understanding Synthetic Aperture Radar Image, London, Artech House, 1998.
2. X. D. Chen, Application of Microwave Passive Remote Sensing in Sea State Monitoring, Beijing, Serveying & Mapping publishing house, 1992.
3. J. F. Mustard, “From planets to crops and back: remote sensing makes sense,” J. Geophys. Res. Plan., vol. 122, no. 4, pp. 794–797, 2017, https://doi.org/10.1002/2017JE005315.
4. B. H. Yang and S. Li, “Remote sense image classification based on CART algorithm,” Adv. Mater. Res., vol. 2914, no. 1731, pp. 2782–2786, 2014, https://doi.org/10.4028/www.scientific.net/AMR.864-867.2782.
5. F. H. Bouzahar, L. Ouerdachi, M. Keblouti, et al.., “The contribution of remote sensing in hydraulics and hydrology, analysis and evaluation of digital terrain model for flood risk mapping,” J. Water Land Dev., vol. 39, no. 1, pp. 17–26, 2018, https://doi.org/10.2478/jwld-2018-0055.