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This paper presents a novel GPS/INS navigation filter design using a combination of Radial Basis Function Network (RBFN) and Particle Swarm Optimization (PSO) techniques, termed PSO-RBFN. The proposed method aims to improve the accuracy of navigation systems by addressing the limitations of traditional Kalman filtering, particularly in scenarios with nonlinear dynamics and measurement uncertainties. The PSO-RBFN mechanism effectively identifies and corrects modeling errors in real-time, leading to significa

Author

khalid nasr

Language

EN