SMCG research on electromagnetic scattering in arid area
-
Fengyun Jiang
Abstract
This article is devoted to the study of electromagnetic scattering characteristics in arid areas, and proposes environmental monitoring and improvement methods. A four-component soil dielectric model was established to study the relationship of soil dielectric constant with soil moisture and frequency. As the Monte Carlo Method combined with Gaussian spectral function was used to simulate the actual dry ground, the Sparse Matrix/Canonical Grid (SMCG) algorithm model based on the surface current equation was established to calculate the electromagnetic scattering coefficient of arid areas. To verify the correctness of the proposed algorithm, the results obtained by SMCG was compared with those calculated by Method of Moments (MOM), which showed great consistency. Many results were obtained by using the algorithm in this paper, based on the measured soil data in the southeastern area of Ejin Banner, Inner Mongolia. It was found that soil moisture content, area roughness and incident electromagnetic wave segment had influence on the scattering echo and showed regular change. The results of this paper are of guiding significance for soil moisture monitoring, desertification control and agricultural planting in arid areas.
-
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
-
Research funding: None declared.
-
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
[1] Q. Q. Guo, J. J. Qu, G. H. Wang, J. H. Xiao, and Y. J. Pang, “Progress of wetland researches in arid and semi-arid regions in China,” Arid Zone Res., vol. 32, no. 02, pp. 213–220, 2015.Search in Google Scholar
[2] X. D. Guan, S. J. Cheng, R. X. Guo, and M. X. Ji, “Review of researches on numerical simulation of soil moisture over the arid and semi-arid region,” J. Arid Meteorol., vol. 32, no. 01, pp. 135–141, 2014.Search in Google Scholar
[3] S. Khanal, A. Klopfenstein, K. C. Kushal, et al., “Assessing the impact of agricultural field traffic on corn grain yield using remote sensing and machine learning,” Soil Tillage Res., vol. 208, pp. 619–623, 2021.10.1016/j.still.2020.104880Search in Google Scholar
[4] X. W. Zhao, S. Pan, Z. C. Sun, H. D. Guo, L. Zhang, and K. Feng, “Advances of satellite remote sensing technology in earthquake prediction,” Nat. Hazards Rev., vol. 22, no. 1, 2021, https://doi.org/10.1061/(asce)nh.1527-6996.0000419.Search in Google Scholar
[5] L. Nhamo, G. Y. Ebrahim, T. Mabhaudhi, et al., “An assessment of groundwater use in irrigated agriculture using multi-spectral remote sensing,” Phys. Chem. Earth, vol. 115, p. 102810, 2020.10.1016/j.pce.2019.102810Search in Google Scholar
[6] D. Sarala and S. Jacob, “Digital image processing – a remote sensing perspective,” Int. J. Innovat. Res. Dev., vol. 3, no. 12, pp. 789–793, 2014.Search in Google Scholar
[7] J. X. Li, M. Zhang, W. Q. Jiang, and P. B. Wei, “Improved FBAM and GO/PO method for EM scattering analyses of ship targets in a marine environment,” Sensors, vol. 20, no. 17, 2020, https://doi.org/10.3390/s20174735.Search in Google Scholar PubMed PubMed Central
[8] G. Ross, “Electromagnetic scattering and its applications,” Opt. Acta, vol. 29, no. 6, 2010, https://doi.org/10.1080/713820916.Search in Google Scholar
[9] R. L. Rowell and R. S. Stein, “Electromagnetic scattering,” Science, vol. 149, no. 3690, pp. 256–259, 1965. https://doi.org/10.1126/science.149.3690.1399.a.Search in Google Scholar
[10] A. M. Tian, Simulation Method of EM Scattering From Layered Rough Surface and Its Application in Snow, Xian, Xidian University, 2019.Search in Google Scholar
[11] X. C. Li and B. D. Zhang, “Comparison research between two EM scattering models for wet sand particle,” J. Ningxia Univ. (Nat. Sci. Ed.), vol. 34, no. 01, pp. 35–39, 2013.Search in Google Scholar
[12] X. Gao, Research on Some Basic Problems of Electromagnetic Scattering of Sand Particle, Ningxia, Ningxia University, 2019.Search in Google Scholar
[13] G. H. Han, Soil Surface Moisture Inversion Research on Salt-Affected Soils by Polarimetric Radar in Arid Areas, Urumchi, Xingjiang University, 2013.Search in Google Scholar
[14] W. Xie, Inversion of Soil Moisture in Arid Area Based on C- and L-Band SAR Images, Xian, Chang’an University, 2019.Search in Google Scholar
[15] R. Wang, L. X. Guo, and A. Q. Wang, “Investigation of electromagnetic scattering interaction between the buried target and the rough surface in different types of soil,” Acta Phys. Sin., vol. 59, no. 5, pp. 3179–3186, 2010, https://doi.org/10.7498/aps.59.3179.Search in Google Scholar
[16] R. E. Caflisch, “Monte Carlo and quasi-Monte Carlo methods,” Acta Numer., vol. 7, pp. 913–916, 1998. https://doi.org/10.1017/s0962492900002804.Search in Google Scholar
[17] C. Bourlier, G. Bergine, and J. Saillard, “Theoretical study on two-dimensional Gaussian rough sea surface emission and reflection in the infrared frequencies with shadowing effect,” IEEE Trans. Geosci. Rem. Sens., vol. 39, no. 2, pp. 379–392, 2001, https://doi.org/10.1109/36.905246.Search in Google Scholar
[18] P. Peng, C. M. Tong, J. S. Bao, J. J. Sun, and D. Li, “Study on the EM scattering from the earth surface based on the 2D rough surface model,” J. Microw., vol. 29, no. 4, pp. 38–42, 2013.Search in Google Scholar
[19] X. Su, Z. S. Wu, X. B. Wang, and F. Dai, “Backscatter analysis of lossy dielectric sea surface using SMCG-PBTG method-comparison with experimental data,” J. Electron. Inf. Technol., vol. 38, no. 2, pp. 486–494, 2016.Search in Google Scholar
[20] Y. H. Wang, Y. M. Zhang, and L. X. Guo, “Investigation of the scattered field from a two-dimensional dielectric target above the planar surface with a Guass beam incidence,” Acta Phys. Sin., vol. 57, no. 9, pp. 5529–5535, 2008, https://doi.org/10.7498/aps.57.5529.Search in Google Scholar
© 2023 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- GPU acceleration of Nystrom type method for solving singular integral equations in H-polarized EM waves scattering by strip gratings
- SMCG research on electromagnetic scattering in arid area
- Design of a compact metamaterial absorber with wide angular stability and polarisation insensitive for C, X and broad Ku band applications
- Design and analysis of novel DGS-loaded low-pass filter with wide stopband
- Design of dual-band BPFs with high selectivity
- A novel non-iterative algorithm for the joint design of transceiver beamforming and surface reflection in an IRS-enhanced MIMO system
- Effects of ground plane on a square graphene ribbon patch antenna designed on a high-permittivity substrate with PBG structures
- Mutual coupling reduction with Peyton Turtle pattern nearfield surface for MIMO patch antenna
- Dual-band open-loop monopole (2 × 1) printed MIMO antenna for 4G and 5G applications
- SIW-cavity based frequency reconfigurable antenna for IoT, WLAN, and 5G applications
Articles in the same Issue
- Frontmatter
- Research Articles
- GPU acceleration of Nystrom type method for solving singular integral equations in H-polarized EM waves scattering by strip gratings
- SMCG research on electromagnetic scattering in arid area
- Design of a compact metamaterial absorber with wide angular stability and polarisation insensitive for C, X and broad Ku band applications
- Design and analysis of novel DGS-loaded low-pass filter with wide stopband
- Design of dual-band BPFs with high selectivity
- A novel non-iterative algorithm for the joint design of transceiver beamforming and surface reflection in an IRS-enhanced MIMO system
- Effects of ground plane on a square graphene ribbon patch antenna designed on a high-permittivity substrate with PBG structures
- Mutual coupling reduction with Peyton Turtle pattern nearfield surface for MIMO patch antenna
- Dual-band open-loop monopole (2 × 1) printed MIMO antenna for 4G and 5G applications
- SIW-cavity based frequency reconfigurable antenna for IoT, WLAN, and 5G applications
