Thickness Measurement for Mountain Glaciers with Water-Rich Ice Based on VHF GPR and PSO-CTM-CFAR Detector

Glaciers and ice caps in High Mountain Asia are changing rapidly in response to climate change, where ice thickness is a key parameter to describe glacier change. However, in high mountain areas of Asia, with the increasing on liquid water content (LWC) of mountain glaciers and formation of water-rich ice layers, the dispersion caused by water-rich ice makes it difficult to directly identify the true location of ice-granite interface through ground penetrating radar data. It is a core challenge for thickness measurement of mountain glaciers with water-rich ice to accurately detect the ice-granite interface. In this paper, to extract ice-granite interface and measure the thickness of mountain glaciers with water-rich ice, we construct a stochastic dispersive medium model of mountain glaciers with water-rich ice based on FDTD algorithm, establish a mixed Weibull noise model to describe to clutters from liquid water in water-rich ice medium and propose an corrected trimmed mean constant false alarm rate (CTM-CFAR) based on particle swarm optimization (PSO) to extract the characteristic of ice-granite interface. Compared with other CFAR, the method proposed in this paper has higher precision and lower measurement error. In addition, with low signal-to-noise ratio (SNR) conditions, the proposed method also exhibits better performance than other CFAR based methods.