Error estimation for an integrated GPSINS system using adaptive neuron-fuzzy technique

Abstract EN

Global Positioning System (GPS) and Strap down Inertial Navigation System (SDINS) can be Integrated Together To Provide A Reliable Navigation System.

In This Paper, A Technique For Error Estimation In A GPS/INS System Based On A Low-Cost Inertial Measurement Unit (IMU) Is Offered.

This Technique Is Composed Of Wavelet Transform (WT) And Adaptive Fuzzy System (AFS).

The Wavelet Decomposition Is Used To De-Noise The Position And Velocity Components Of The GPS And INS Outputs.

An AFS Is Introduced In This Paper To Estimate The Position And Velocity Errors In The Integrated System In Order To Provide Accurate Navigation Information About The Moving Vehicle.

Several Data Sets Are Processed In This Paper, Where The Simulation Results Are Based On Matlab7 Programming Language.

Six AFS Networks Are Used To Process The Position And Velocity Components.

The Average Error Value Per Sample Was 0.0142, 0.0443, And 0.0108 M For Position In X, Y, And Z Axes Respectively And 0.0077, 0.0223, And 0.0269 M/S For Velocity In North, East, And Down Directions Respectively.