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 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 (GPR) 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 article, 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 a 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 article 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.