Cloud bottom height estimation methods for optical imaging terminal guidance

Shuai Liang, Mengying Liu, Zhongyang Wang, Tianxu Zhang
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Abstract

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%.
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光学成像末制导的云底高度估计方法
利用国内外气象卫星资料,开展可用于光学成像终端制导的业务区域气象研究。针对云覆盖区域的攻击分为以下两种场景:1.云覆盖区域。云为中高云,由于这类云层的云底高度比较高,一般在2500米以上,不会对光学成像末制导产生太大影响;2. 云覆盖率低但不完全覆盖,可以对云进行检测和分割,避免云击中目标。我们使用机器学习算法训练模型将云分为多层云和单层云,分类准确率达到82.1%。然后,对于单层云,有两种方法来估计云底高度:1。我们可以利用Aqua气象卫星的MODIS数据来识别不同属性的云进行云高估算。2. 利用云的物理特性可以直接计算单层云的高度,平均计算误差为16.5%。
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