Data Fusion Applications In Engineering And Research

In this paper, the parameter estimation and the application of it in the engineering are focused on. At first, the system of data fusion and some basic principles, theories and methods are introduced. In Chapter Two, static parameter estimation is discussed which includes last-square estimation, maximum likelihood estimation, minimum variance estimation, Bayes estimation and consensus measure method. In Chapter Three, dynamic parameter estimation is discussed: in the beginning, discrete and distributed kalman filter is presented; then the differences between distributed kalman filter with feedback and one without feedback are compared; at last distributed kalman filter is promoted on the basis of the consensus measure theory, which is proved to be effective. And its 時eal-time is presented theoretically.. In the last Chapter, some applications of data fusion in the engineering are researched: in Section One, to aim at the method provided by referencel6l which is hardly feasible in practice ,the method of data fusion based on information distribution theory is presented, which is characterized by simplicity and high efficiency; the system of temperature measurement in the high temperature kilns, to aim at traditional imaging temperature measurement which usually uses the method of digital image processing to deal with signals and neglects relationship between three kinds of colors, kalman filter is applied to fusing signals of three kinds of color. Stimulation proved that its effect is greatly promoted.