Penerapan Metode Kalman Filter Slow-Fast Differential Untuk Meningkatkan Kerapatan Dan Nilai Curah Hujan Dengan Menggunakan Signal To Noise Ratio Pada Hub VSat

Abstract

Abstract Rainfall measurement must be carried out, because rain is an essential phenomenon for human living. Generally, rainfall is measured using ground measurement (rain gauge), weather radar, and weather satellite. In this study, we exploit the potential of estimating rain fall by down SNR Ku-Band (14 GHz) wave on VSAT Hub using slow-fast differential kalman filter. This method using two kalman filters, ST (Slow Tracker) and FT (Fast Tracker). ST is slower, not more reactive than FT. Combination of those filters can detect and estimate rainfall.  Rainfall estimation obtained from down SNR will be compared with rainfall measurement from ground measurement of rain gauge. Hub and rain gauge  are close together and located in Kemayoran, Jakarta Pusat. This Area is still in coverage area of rain gauge between 250 m2 and 3000 m2. This research was successful in detecting ongoing rain. The rainfall estimation results obtained had a correlation coefficient of 0.9648 and a root mean square error of 4.418 Key words: Rain fall, Ku-band, signal to noise ratio, slow-fast differential kalman filter