An application of fuzzy sets in real time filtering problems

The human decision-making task is modeled with fuzzy sets and the Kalman filter updates to the state vector are weighted using fuzzy functions. Results of the study show that the use of fuzzy set models gives results comparable to those requiring human assistance, e.g. lock on to false targets, and better results when the problem is caused by noise and/or bias, or unexpected errors in the state vector at initial acquisition.