一个SARAL/AltiKa波形聚类工具的简短演示

Surajit Dutta, Suvajit Ghosh, P. Thakur
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引用次数: 0

摘要

本文描述了一个SARAL/AltiKa波形聚类的分类工具。该工具是使用Python脚本制作的。雷达测高系统(例如SARAL/AltiKa)通过计算雷达脉冲的卫星到地面的往返时间来测量从卫星中心到目标表面的距离。高度计的波形表示地球表面反射到卫星天线的能量与时间的关系。该工具将测高波形数据聚集到所需的组中。对于聚类,我们使用进化最小化索引函数(EMIF)和k-means聚类机制。其想法是开发一个简单的接口,该接口将来自文件夹的测高波形数据作为输入,并为每个波形提供单个值(使用EMIF算法)。这些值将进一步用于聚类。这是一个简单的轻量级工具,用户可以很容易地与它进行交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A brief demonstration of a tool for SARAL/AltiKa waveform clustering
This article describes a classification tool to cluster SARAL/AltiKa waveforms. The tool was made using Python scripts. Radar altimetry systems (e.g., SARAL/AltiKa) measures the distance from the satellite centre to a target surface by calculating the satellite-to-surface round-trip time of a radar pulse. An altimeter waveform represents the energy reflected by the earth’s surface to the satellite antenna with respect to time. The tool clusters the altimetric waveforms data into desired groups. For the clustering, we used evolutionary minimize indexing function (EMIF) with k-means cluster mechanism. The idea was to develop a simple interface which takes the altimetry waveforms data from a folder as inputs and provides single value (using EMIF algorithm) for each waveform. These values are further used for clustering. This is a simple light weighted tool and user can easily interact with it.
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