Open AccessFILTER ADAPTIF GPS PADA SISTEM DOWNLINK DATA
Author(s) -
Agus Basukesti,
Bangga Dirgantara Adiputra
Publication year - 2017
Publication title -
angkasa
Language(s) - English
Resource type - Journals
eISSN - 2581-1355
pISSN - 2085-9503
DOI - 10.28989/angkasa.v8i2.125
Subject(s) - global positioning system , precision lightweight gps receiver , computer science , time to first fix , assisted gps , real time computing , gps/ins , gps disciplined oscillator , kalman filter , receiver autonomous integrity monitoring , filter (signal processing) , gps signals , noise (video) , remote sensing , telecommunications link , geography , gps receiver , telecommunications , computer vision , artificial intelligence , image (mathematics)
GPS (Global Positioning System) is a system used for navigation and positioning with the help of 32 satellites that orbit the earth. GPS satellites emit radio waves to activate the GPS receiver on the Earth to determine the exact location, speed and time for all weather conditions. Currently, GPS has a vital role in navigation drone. However GPS have a lot of noise, it is necessary to overcome the noise filter on the GPS. In this research conducted a simulation of adaptive algorithm in extracting data from the GPS sensor. The method in this research is the Kalman Filter. From the identification and simulation can be concluded that the adaptive algorithm is designed to work well and need to be implemented on the downlink system. The simulation results showed that the error of algorithm has convergent properties are increasingly shrinking.