Multisensor measured data fusion based on Kalman filtering

Because least square data fusion can not explicit consider the measurement uncertainties,the paper proposes the method of multisensor measured data fusion based on Kalman filtering.The method not only considers measurement uncertainties and also realizes processing the single measured datum and numbers of data so that customs choose efficient method of data fusion according to measured data.Finally,the method robustly identifies the noise variance and outliers based on the Mahalanobis distance.Experimental results demonstrate that the method produces better quality fusion surface.