A Kalman Filter for RSSI Distance approximations

Question

I'm currently working on a project that makes use of RSSI signals to determine a users distance from between three beacons. Whilst I have the rough triangulation formulas working, I'm trying to make something a lot more accurate.

Through all my research, I have discovered Kalman filters. From what I've been reading about them, they seem to be just what I'm wanting to use. However, all of the examples I have found have been fairly complex and difficult to understand.

Has anyone ever used a Kalmon filter combined with an RSSI signal before? Is anyone capable of point me, or explaining to me, how a Kalmon filters work in a simple way?

Answer 1

Has anyone ever used a Kalmon filter combined with an RSSI signal before?

Yes, see for example: RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

Is anyone capable of point me, or explaining to me, how a Kalmon filters work in a simple way?

The most human readable intro with examples I have found so far is the SIGGRAPH Course Pack.