Fuzzy multiple model tracking algorithm for manoeuvring target

Abstract

This paper develops a tracking algorithm for maneuvering target based on fuzzy logic inference (FMMTA). In place of the model probability computed intricately in the IMM, filtering measurement innovations are tackled with the innovation covariance, and the results are used as the input to a fuzzy inference system to get the matched degrees for each filtering model in the model set designed. With the matched degrees, the estimation from each filtering is weighted to obtain the maneuvering target's overall estimation and its covariance. The performance of FMMTA is tested via Monte Carlo simulation, and the result expresses its validity and its promise.