Method for identifying clouds of cloud detection radar

A cloud measuring radar and recognition result technology, applied in the field of neural network and meteorological remote sensing, can solve problems such as easy misjudgment, and achieve the effect of overcoming easy misjudgment, solving the problem of parameter acquisition, and adaptive learning and optimization ability.

Pending Publication Date: 2020-02-21
SHANGHAI RADIO EQUIP RES INST
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AI Technical Summary

Problems solved by technology

This method overcomes the shortcoming of easy misjudgment of the threshold method, solves the parameter acquisition problem of fuzzy logic, and has adaptive learning optimization ability

Method used

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  • Method for identifying clouds of cloud detection radar
  • Method for identifying clouds of cloud detection radar
  • Method for identifying clouds of cloud detection radar

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Embodiment Construction

[0040] The following is attached figure 1 A specific embodiment of the present invention will be described in detail.

[0041] Such as figure 1 As shown, the method for cloud-measuring radar to identify clouds provided by the present invention includes the following steps:

[0042] Step S1. Extract cloud characteristic parameters from the cloud survey radar observation information sample data as input, and cloud class as output, establish a cloud physical quantity learning library for autonomous learning, quantify the cloud classification value, and perform quantification according to each type of cloud Establish the cloud feature parameter matching rules of each type of cloud;

[0043] Cloud classification products obtained by obtaining cloud vertical and horizontal cloud characteristics, whether precipitation occurs, cloud temperature and other information based on cloud survey radar remote sensing data. Considering that the physical properties of clouds vary greatly in differ...

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Abstract

The invention discloses a method for identifying clouds of a cloud detection radar. The method comprises the following steps of establishing a cloud physical quantity learning library for autonomous learning, and a matching rule that cloud characteristic parameters belong to a certain class of cloud; establishing a fuzzy logic function that each cloud characteristic parameter belongs to each typeof cloud and a corresponding fuzzy logic function parameter; setting an influence weight, calculating the probability that different cloud characteristic parameters belong to a certain type of cloud by adopting a weighted normalization method, and obtaining a calculation result of cloud type identification according to the matching rule; calculating an error of a cloud class identification result,and optimizing the fuzzy logic function parameter and the influence weight by utilizing the partial derivative loop iterative operation; and for the new cloud measurement radar observation information, calculating the cloud class identification result, and updating the cloud physical learning library to realize the cyclic autonomous learning and updating of the fuzzy logic function parameter andthe influence weight. The method overcomes the defect that a threshold method is prone to misjudgment, solves the problem of parameter acquisition of fuzzy logic, and has the adaptive learning optimization capability.

Description

Technical field [0001] The invention relates to the fields of meteorological remote sensing and neural network, in particular to a cyclic autonomous learning cloud recognition method using cloud measurement radar. Background technique [0002] Clouds play an important role in regulating the radiation balance and water vapor cycle of the earth-atmosphere system. Different cloud types have different dynamic processes and physical characteristics, resulting in different radiation scattering characteristics, cloud thickness, range and other macroscopic parameters, and clouds. The inversion of microscopic parameters such as particle size, shape, number concentration, ice water content, particle spectrum distribution, etc. are also closely related to the cloud phase state. Climate model studies have shown that the difference in cloud characteristic parameters of different types of clouds in the model will lead to large differences between the simulation results, making the unreasonable...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G01S13/95G01S7/41
CPCG01S13/955G01S7/418G06V20/13G06F18/24Y02A90/10
Inventor 丁霞王平王海涛
Owner SHANGHAI RADIO EQUIP RES INST
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