Retrieving the troposphere duct by using ground-based radiometric profiler in South Coast in China

Coastal areas worldwide are known to be especially `rich' in super refractive layers and waveguides that affect microwave propagation. Radiosonde data of Xiamen and Haikou in south coast in China were chosen to analysis the rule and characteristics of the troposphere duct in this paper. Based on the historical data, improved learning vector quantization neural network method (LVQ) and improved Radial Basis Function neural network method (RBF) is used to retrieving the troposphere duct. The two algorithms are presented by using the brightness temperature detected by the ground-based multi-channel microwave radiometer both in zenith and gradient angles. Feasibility of this method is demonstrated with the results by the measure data. Ground-based multi-channel microwave radiometer has been proven to be a powerful tool to sensing troposphere duct, which can perform continuous troposphere duct profiles and provide information of electromagnetism environment for the application of radar, communication and navigation systems.