Open AccessWaveform re-tracking analyses with Fuzzy Logic on altimetry satellite data in Natuna Waters
Author(s) -
Rozeff Permana,
Bisman Nababan,
James P. Panjaitan
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/429/1/012042
Subject(s) - altimeter , waveform , fuzzy logic , tracking (education) , computer science , satellite , standard deviation , sea surface height , remote sensing , data mining , mathematics , artificial intelligence , statistics , geography , engineering , telecommunications , psychology , pedagogy , radar , aerospace engineering
Waveform re-tracking analyses have been proven to increase the accuracy of sea surface height (SSH) estimation from satellite altimeters specifically in coastal areas. However, each re-tracking algorithm has its strengths and weaknesses so that no dominant algorithm can be applied to any water condition. The study purpose was to obtain the best SSH estimation from altimeter satellite data using waveform re-tracking analyses with fuzzy logic system. The fuzzy logic system was used to select the best SSH values from the results of waveform re-tracking analyses. The data used in this study were level-2 SGRD data from Jason-2 and Jason-3 in Natuna Waters in 2016-2018. Waveform re-tracking with fuzzy logic system can reduce standard deviation of SSH up to 23.3 cm from the on-board (oceanic) algorithm standard deviation. The highest Improvement Percentage (IMP) value from each observation track was constantly generated by re-tracking with fuzzy logic system up to 70.3%. The result of this study showed that this analysis can produce SSH values with the best accuracy in each track observation.