Rainfall intensity grade inversion method based on combination of multiple characteristic parameters of occlusion area of navigation radar image

Abstract

The invention provides a rainfall intensity grade inversion method based on combination of multiple characteristic parameters of an occlusion area of a navigation radar image. Firstly, an off-line observation experiment is carried out to determine the fitting relation between the rainfall intensity and the occlusion-area zero intensity percentage and the fitting relation between the rainfall intensity and the echo-intensity mean value; secondly, a to-be-inverted original image is pretreated, and the characteristic parameters, namely the zero intensity percentage and the echo-intensity mean value, of the occlusion area are calculated; finally, the zero intensity percentage and the echo-intensity mean value substitute into the fitting relation between the rainfall intensity and the occlusion-area zero intensity percentage and the fitting relation between the rainfall intensity and the echo-intensity mean value, and two rainfall-intensity values are obtained; finally the average value ofthe obtained two rainfall-intensity values is obtained to serve as the final rainfall intensity, and the rainfall intensity grade is thus determined. The effect is verified through actually measured data, the overall correct rate of the rainfall intensity grade inversion reaches 85%, and the method provides a novel and convenient way for the rainfall measurement in the course of navigation.

Description

technical field [0001] The invention relates to a rain intensity level inversion method based on the combination of multiple characteristic parameters in the occlusion area of ​​a navigation radar image, which belongs to the technical field of marine remote sensing, and specifically relates to the inversion calculation of the rainfall intensity level using the combination of multi-characteristic parameters in the occlusion area of ​​a navigation radar image in the field of ocean remote sensing technology. Background technique [0002] The ocean, which accounts for 71% of the earth's surface area, is rich in resources. Since the 21st century, humans have gained a deeper understanding of the special space of the ocean. The exploration of marine resources and the monitoring of the marine environment are crucial to promoting the sustainable development of the marine economy and strengthening the marine ecology. The construction of civilization is of great significance to promote...

AI Technical Summary

Problems solved by technology

[0008] The existing rainfall estimation technology is used in navigation, which has poor real-time performance and is relatively cumbersome. If the navigation radar image is directly used to estimate the rainfall at sea during navigation, the equipment can be simplified to a certain extent, resources can be saved, and cost, maintenance Both have advantages in terms of timeliness and

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