Implementasi Logika Fuzzy pada Kekuatan Sinyal yang Diterima Antena Viasat X-Band

Afif Nuur Hidayat, Bagus Fatkhurrozi, Ibrahim Nawawi

Abstract

The data that the antenna receives during satellite data acquisition has a signal strength that is affected by the antenna's movement at an elevation and azimuth angle. Every change in the two angles causes the signal strength received by the antenna to change. Signal strength calculation is important to be able to ensure satellite data is received well. Fuzzy Mamdani's logic as a method that can be used to calculate uncertain variables will be implemented in the calculation of the signal strength received by the Viasat X-Band antenna when the acquisition process of Aqua satellite data takes place. The results of the calculation of fuzzy mamdani logic by testing 6 signal strength data obtained from the Aqua satellite track analysis owned by LAPAN are shown in the percentage of errors, among others: DOY 197 of 1.33%; DOY 213 by 2.89%; DOY 259 of 1.93%; DOY 304 of 1.18%; DOY 320 by 4.73%; and DOY 357 of 2.27% and the average error (overall) of the entire data tested was 2.39%. This shows that the mamdani fuzzy logic is suitable for use in calculating the signal strength received by the Viasat X-Band antenna.

Keywords

Antenna; Elevation; Azimuth; Signal; Fuzzy

Full Text:

PDF

References

Lucyszyn, S. (2006). Frequency Spectrums and Applications. Imperial College

Nasution, H. 2001. Orbit Satelit dan Ketinggiannya. Jurnal Berita Dirgantara, 2(1), 28-30.

Rahman, A. (2008). Sistem Tracking Stasiun Bumi Satelit Orbit Rendah. Jurnal Berita Drgantara, 9(4), 95-99.

Prasesiati, V. (2003). Perangkat Lunak untuk Perhitungan Sudut Elevasi dan Azimuth Antena Stasiun Bumi Bergerak dalam Sistem Komunikasi Satelit Geostasioner. Jurnal Unitas, 11(2), 73-85

Hua, G., Ma, Y., & Jirigele. (2015). Studies on Satellite Antenna Gain Measurement System Based on Comparison Method. Key Project of National Natural Science Foundation of China, 242-244

Modi, A.Y., Mehta, J., & Pisharody, N. (2013, Mei). A Faster Approach for Design of Optimum Gain L-Band Pyramidal Horn using Adaptive Neuro Fuzzy Inference System (ANFIS). 5th International Conference on Computational Intelligence and Communication Networks (pp 37-40). IEEE.

Basuki, O.A., Budi, E.P., & Sari, S.N. (2016). Analisis Link Budget dengan Perbedaan Sudut Azimuth dan Elevasi pada Proses Pointing menggunakan Two Line Elements dan Perhitungan Matematis pada Satelit Telkom-1 dan Telkom-2. Jurnal EECCIS, 10(1) : 33-38

Saelan. (2009). Logika Fuzzy. Makalah IF2091 Struktur Diskrit Tahun 2009.

Ying. (2001). Conditions on General Mamdani Fuzzy Controllers as Nonlinear, Variable Gain State Feedback Controllers with Stability Analysis. IEEE (1), 1265-1270.

Das, B.K., Jiang,J., & Rao, J.N.K. (2004). Mean Squared Error of Empirical Predictor. The Annals of Statistic, 32(2), 818-840

Article Metrics

Abstract view: 68 times
Download     : 9   times

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Refbacks

  • There are currently no refbacks.