Research On Multi-sensor Data Fusion Algorithm Based On Fuzzy Set And Statistical Theory

Application of multisensor data fusion spans a broad range that includes military and civilian. Multisensor data fusion is one popular research field in domestic and foreign scientific and technological circles. The main job in this thesis can be summarized as follows:First, focusing on the multi-sensors measurement on the same characteristic index from different directions, a multi-sensor data fusion algorithm based on optimal fusion set is proposed. The optimal fusion set is defined to obtain the valid observation data, in which the consistent fusion degree and the distribution degree of sensors are measured by using fusion degree matrix of the optimal fusion set. And then the weights of the valid observation data in the fusion process are reasonably assigned. So that the final expression of data fusion and estimation is obtained. The data fusion results show that this method not only has higher fusion precision, but also has excellent ability of stableness.Second, a new method was proposed for dealing with conflicting evidence when the Dempster combination result can not identify the actual conditions. The method combines the advantages of justification of evidence information and combination rules. The credibility of the evidence is computed by the reliability matrix which is introduced though by the concepts of the conflict factor and coherence coefficient. And the value of credibility degree was further changed into weight coefficient which reflects the global reliability degree for the evidence. According to the weight coefficient, the basic probability assignments were reallocated, and then the final combination results can be obtained by the advanced synthesis formula. The data fusion results shows that the new method has better reliability, and higher convergent speed compared to the other methods.At last, this thesis discusses a distributed system of multi-sensors and its two-level fusion model that is applied to measure of greenhouse environment, as well as the hybrid algorithm based on D-S theory and expert system. The method can improve the accuracy of tomato growing environment measurement, and regulate the temperature, humidity and illumination in greenhouse, so that it reaches ideal condition. The results show that this method is effectiveness.