How Can the Kalman Filter Improve Position Sensor Data Analysis?

[jgvicke]

Hey everyone,

I have a system that I know the x,y,z position and the alpha,beta,gamma euler rotation of an object in space at known intervals. I need to use a filter on this data to reduce the error of the measurements, and it would be nice to be able to predict future movement. I understand that the Kalman filter is the way to go about this, but I havn't been able to find a good example, tutorial, etc that makes much sense to a beginner.

I also need to filter position sensor data that has an x and y component. I will have a position measurement from this sensor at a given time interval as well.

Can someone give me a direction to go, a suggestion for material to look at, etc? Any help would be greatly appriciated.

 

[D H]

This might be of some help: http://cs.unc.edu/~tracker/media/pdf/SIGGRAPH2001_CoursePack_08.pdf

I also suggest you go to a library. Brown and Hwang (1992), “Introduction to Random Signals and Applied Kalman Filtering” is a good start.