Self-adaptive dry and wet distinguishing method based on multiple statistics of microwave link

Abstract

The invention discloses a self-adaptive dry and wet distinguishing method based on multiple statistics of a microwave link. The correlation degree between statistical parameters of link attenuation data and dry and wet moments is analyzed by adopting a statistical means, the statistical parameters with high correlation degree are adaptively selected as feature vectors by taking the correlation degree as a criterion, and dry and wet distinguishing in a weather change process is realized by utilizing classification algorithms such as a support vector machine and the like. According to the self-adaptive dry and wet distinguishing method, the dry and wet moments can be distinguished through microwave link signal changes, continuous weather monitoring can be effectively achieved, and the self-adaptive dry and wet distinguishing method has important significance in further improving the microwave link rain measurement precision, improving the application benefits of the microwave link rain measurement method and the like.

Description

technical field [0001] The invention relates to the field of meteorological information processing and application, in particular to an adaptive wet-dry distinction method based on microwave link multi-statistics. Background technique [0002] As one of the most active weather phenomena in the troposphere that is closely related to people's lives, precipitation phenomena are closely related to people's lives. With the continuous development of various meteorological and hydrological related businesses, not only in the field of meteorology, more and more There is an increasing demand for access to precipitation-related information in the field. At the same time, under the trend of more and more refined meteorological guarantees, people have higher requirements for the quality of precipitation information. Therefore, real-time, accurate and fine monitoring of precipitation is of vital significance in both meteorological and hydrological research and government early warning d...

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Problems solved by technology

[0004] Purpose of the invention: The present invention aims at the problems that most communication links receive signals with complex time distribution rules, and it is difficult to accurately distinguish between dry and wet moments, resulting in difficulties in accurately extracting rain attenuation reference values ​​and limited rain intensity inversion accuracy, and proposes a microwave-based In the self-adaptive dry-wet distinction method of link multi-statistics, the present invention uses statistical means to analyze the correlation between microwave link observation data attenuation statistical parameters and rain (wet weather) / no rain (dry weather), and Select statistical parameters with high correlation as eigenvectors to establish an adaptive method for distinguishing dryness and wetness with multiple statistical parameters, and provide basic technical support for further improving the precision of microwave link rain measurement and improving the application efficiency of microwave link rain measurement methods

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