Sensor fusion of imu and gps using extended kalman filter

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Hi, i am working on sensor fusion fo imu and gps to have accurate position on world coordinates.
I have worked on 2D implementation in C++ but now i am facing it difficult to extend it to 3D as the parameters are really complex to add as i am getting confused how to make my state space and other matrix for predict and update, Plus fusing the data is also an issue how to introduce the data in the filter for 3D, I need to fuse (X Y Z) position of IMU also yaw, roll with (Longitude and Latitude [X Y]) position of GPS.
If anyone of you have implemented it or have leads to that where i can look or take any guide that would be a big help.
Thanks!

What I have tried:

i have worked with 1d and 2d kalman implementation for linear systems.

Posted 28-Mar-19 5:36am

Member 14181061

Updated 28-Mar-19 8:35am

Richard MacCutchan

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Rick York · Answer 1 · 2019-03-28T08:36:00

Solution 1

Do a search for GPS at this site. There are a good number articles on the topic. The search box is in the upper right corner on the first page of this site.

Posted 28-Mar-19 8:36am

Rick York

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Member 14181061 28-Mar-19 15:14pm

Already got articles and research papers explaining the scenario, but my focus is more towards programming, increasing the dimensions, widening of state, predict and update of EKF.

Rick York 28-Mar-19 15:20pm

This is a site for programmers and the articles here are about programming.

Member 14181061 29-Mar-19 4:43am

Thanks for your input, i will look for it.