Comparing Kalman Filter and Dynamic Adaptive Neuro Fuzzy for Integrating of INS/GPS Systems | ||
| Engineering and Technology Journal | ||
| Article 6, Volume 34, 1A, January 2016, Pages 61-72 PDF (883.65 K) | ||
| DOI: 10.30684/etj.34.1A.6 | ||
| Authors | ||
| Sameir A. Aziez; Huda Naji Abdul-Rihda | ||
| Abstract | ||
| Global Positioning System (GPS) and Inertial Navigation System (INS) technologies have been widely used in a variety of positioning and navigation applications. Both Systems have their unique features and shortcomings. Hence, combined system of GPS and INS can exhibit the robustness, higher bandwidth and better noise characteristics of the inertial system with the long-term stability of GPS, Integrated together are used to provide a reliable Navigation System. This paperwill compare the performance of Kalman filter and Dynamic adaptive neuro fuzzy system for integrated INS/GPS systems. The Simulation Results by Matlab7 Programming Language showed great improvements in positioning, gives a best results and reduce the root mean square error (r.m.s.) when used Dynamic adaptive neuro fuzzy system rather than Kalman filter. | ||
| Keywords | ||
| Kalman Filter; Dynamic adaptive neuro fuzzy system; GPS System; INS System | ||
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