Cloud bottom height estimation methods for optical imaging terminal guidance

被引:0
|
作者
Liang, Shuai [1 ]
Liu, Meng [1 ]
Wang, Zhongyang [1 ]
Zhang, Tianxu [1 ]
机构
[1] Huazhong Univ Sci & Technol, Wuhan, Peoples R China
关键词
Cloud bottom height estimation; cloud classification; meteorological satellite; machine learning;
D O I
10.1117/12.2535716
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We use domestic and foreign meteorological satellite data to carry out the research of Operational Regional meteorology which can be used for optical imaging terminal guidances. Attacks on areas covered by clouds can be divided into the following two scenarios: 1. Clouds are medium-high clouds, because the cloud base height of this kind of cloud layer is relatively high, generally more than 2500 meters, it will not have much influence on the optical imaging terminal guidance; 2. With low cloud coverage but not completely covered, the cloud can be detected and segmented, avoiding the cloud to hit the target. We use machine learning algorithm training model to divide the cloud into multi-layer cloud and single-layer cloud, and the classification accuracy reaches 82.1%. Then for single-layer clouds, there are two methods to estimate the cloud bottom height: 1. We can use the MODIS data of the Aqua meteorological satellite to identify clouds of different attributes for cloud height estimation 2 The height of single layer clouds can be calculated directly by using the physical characteristics of clouds, the average calculation error is 16.5%.
引用
收藏
页数:7
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