Non-invasive Measurement of Sea Ice Thickness Using Low Frequency EM Waves
Abstract
Measurement of sea ice thickness is of great importance for safety of navigation and for monitoring the environment, climate and geophysical information. In this research, we propose and investigate a novel concept of measuring sea ice thickness in a non-destructive way through electromagnetic field measurements, and in addition, also estimating the dielectric properties of sea ice. The method involves measuring electric and magnetic fields in the near field zone and estimating the thickness and dielectric properties using deep learning. First, we have developed several analytical methods to simulate an air- sea ice- sea water environment, assuming they form a planar three-layered system. The planewave reflection coefficient, which is a strong function of the thickness and dielectric constant of sea ice bulk, is calculated first, and the expressions are embedded into the source equation of a horizontal electric dipole. A model of sea ice has been developed whose dielectric functions are varied across each layer with changing thickness and age of sea ice and has been used to model the sea ice bulk in the three-layered system. For data acquisition, the source is placed at the air - sea ice interface, and the receiver is swept along a predefined direction across the sea ice bulk. The receiver height can be kept fixed or can be varied as a constant function of wavelength, but for all cases, the -component of the E and H fields appear to show clear dependence with the changing parameters of sea ice. The analytical results are verified with multiple independent calculations and with the help of a finite element simulation software. Afterwards we try to exploit this dependence by forming a deep learning dataset, composed of the normalized field components, operating frequency, and the thickness and dielectric properties of sea ice.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 30, 2022
- Accession Number
- AD1173083
Entities
People
- Imrul Hasan
- M. Saif Islam
- Mohammad A. Haque
- Sadman Shafi