A novel data fusion method based on measurements summation for multisensor system

Abstract

Aiming at the model of linear time invariant for the target tracking system, this paper develops a novel data fusion method based on measurements summation for multisensor system. It effectively uses the characteristics of statistical parameters which can be calculated out of line for linear time invariant(LTI) system Kalman filter, and the calculated form of measurements summation of Kalman filter state estimation under Linear Minimum Mean Square Error (LMMSE) estimate. Then the fusion algorithm of traditional order filter is transformed into the novel form of initial state estimation and all the measurements weighted summation. Compared with the traditional order filter fusion algorithm, the novel fusion estimator not only has the same optimal fusion estimation accuracy, but also can save lots of running time through calculating weighted coefficient out of line. Simultaneously, it still has the better potential of processing delay measurements fusion estimation. The theoretical analysis and computer simulation both indicate that this algorithm is valid and advantageous.