#TITLE_ALTERNATIVE#
In each GPS time series data, there are signals which exist and affect the result that has been received. Those components will form certain pattern in time series. Basically, time series has periodic component which commonly not being able to be detected directly. To detect this periodic component...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/14487 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | In each GPS time series data, there are signals which exist and affect the result that has been received. Those components will form certain pattern in time series. Basically, time series has periodic component which commonly not being able to be detected directly. To detect this periodic component in time series, there is a way which is called spectral analysis. The purpose of spectral analysis is to detect which periodic component that dominantly affect the time series. With acknowledge periodic component in a time series, we can know the characteristic of the time series and later, we can determine how many parameters will be needed to do curve fitting. There are two approximations in fitting, it is either linier fitting only or linier fitting with including periodic component. As a comparison between these two methods, we need to estimate displacements velocity rate in a year. From the analysis that has been done, the result is that the difference displacements velocity rate between these two methods is 3.7 milimeters per year. |
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