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Multi-layered snowpack refractive index estimation based on optical path difference compensation
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DOI：10.1080/01431161.2025.2586473.png)
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Abstract
En 中文
This paper presents a novel method for simultaneously estimating the refractive indices and refining the layer depths of multiple layers within a snowpack, using an analytical model combined with the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. This method improves upon traditional techniques that estimate the refractive index layer by layer and helps prevent error propagation. It minimizes the difference in layer depth coordinates between the actual tomogram and a simulated one, created with the same SAR system settings. The method is validated on both simulated and experimental data, demonstrating its ability to simultaneously retrieve refractive indices and layer depths, with the estimated refractive indices exhibiting less than 22.3% error compared to those derived from in-situ measured density.
Keywords:
Refractive index
electromagnetic wave propagation
Multi-objective particle swarm optimization algorithm (MOPSO)
sar tomography
snowpack
Journal
IF:
2.6
Papers:
1.2W
Citations:
2.7W