Algoritma Adaptif Sistem Downlink Menggunakan Recursive Least Square (RLS)

Agus Basukesti, Bangga Dirgantara


GPS (Global Positioning System) is the popular system for navigation which assistance 32 satellites orbiting the earth. Currently, tracking positions using the Global Positioning System (GPS) is one of the best positioning tracking methods. However, GPS has a lot o f noise, so filters are needed to handle with noise on GPS. In this research, the simulation is done to extract data from GPS sensors using RLS algorithm. From the results o f identification and simulation, it can be concluded that the algorithm works well and need to analyze the advantages and disadvantages to be implemented on the downlink system designed. From the simulation results obtained that error estimation is convergent that is the longer the smaller.


Adaptif, RLS, Error


J. W. Chaffee and J. S. Abel, “The GPS filtering problem,” Position Location and Navigation Symposium, 1992. Record. 500 Years After Columbus - Navigation Challenges of Tomorrow. IEEE PLANS ’92., IEEE. pp. 12-20, 1992.

C. Hide, T. Moore, and M. Smith, “Adaptive Kalman filtering algorithms for integrating GPS and low cost INS,” Position Location and Navigation Symposium, 2004. PLANS 2004. p p .227-233, 2004.

X. Mao, M. Wada, and H. Hashimoto, “Nonlinear filtering algorithms for GPS using pseudorange and Doppler shift measurements,” Intelligent Transportation Systems, 2002. Proceedings. The IEEE 5th International Conference on. pp. 914-919, 2002.

I. M. Taylor and M. A. Labrador, “Improving the energy consumption in mobile phones by filtering noisy GPS fixes with modified Kalman filters,” Wireless Communications and Networking Conference (WCNC), 2011 IEEE. pp. 2006-2011, 2011.

L. Wu, H. Ma, W. Ding, Q. Hu, G. Zhang, and D. Lu, “Study of GPS Data De-Noising Method Based on Wavelet and Kalman Filtering,” Circuits, Communications and System (PACCS), 2011 ThirdPacific-Asia Conference on. pp. 1-3, 2011.

S. Yamaguchi and T. Tanaka, “GPS Standard Positioning using Kalman filter,” SICE-ICASE, 2006. International Joint Conference. pp. 1351-1354, 2006.

M. Zahaby, P. Gaonjur, and S. Farajian, “Location tracking in GPS using Kalman Filter through SMS,” EUROCON 2009, EUROCON'09. IEEE. pp. 1707-1711, 2009.

Article Metrics

Abstract view: 252 times
Download     : 113   times

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


  • There are currently no refbacks.