The　integrated　navigation　system　that　combines　the　global　positioning　system　(GPS)　and　the　inertial　navigation　system　(INS)　has　attracted　widespread　attention.　In　order　to　improve　its　positioning　and　navigation　accuracy,　Kalman　filtering　algorithms　are　usually　used　to　process　navigation　data.　This　paper　combines　fuzzy　control　theory　with　Kalman　filter,　and　proposes　an　integrated　navigation　algorithm　based　on　fuzzy　control　theory,　specifically　observing　each　component　of　the　residual　error,　using　multiple　fuzzy　inference　systems　to　modify　the　measurement　noise　variance　matrix　to　approximate　the　real　noise　characteristic.　Through　multiple　simulation　experiments,　the　results　show　that　the　algorithm　can　effectively　suppress　the　filtering　divergence.　©　2020　The　Institution　of　Engineering　and　Technology.