This　paper　is　concerned　with　the　challenging　problem　of　joint　channel　estimation　and　data　detection　for　high　mobility　multiple-input　multiple-output　orthogonal　frequency　division　multiplexing　systems.　We　propose　a　new　iterative　channel　estimation　and　detection　scheme,　which　reduces　the　unexpected　effects　of　both　detection　errors　and　channel　estimation　errors.　Detection　errors　in　channel　estimation　are　analyzed　and　transformed　as　part　of　the　noise.　To　filter　this　equivalent　noise　by　Kalman　estimator,　we　derive　the　covariance　of　both　the　channels　and　data　errors　in　detection.　Besides,　we　propose　a　new　detection　algorithm　with　an　optimized　weight　to　minimize　the　detection　error　caused　by　channel　estimation　errors.　To　obtain　this　optimized　weight,　the　error　covariance　of　the　estimated　channels　is　derived　from　the　error　estimate　covariance　matrix　in　Kalman　estimator.　Simulation　results　are　presented　to　demonstrate　the　significant　performance　improvement　in　joint　channel　estimation　and　data　detection　with　the　proposed　iterative　scheme.