Abstract: Rainfall is an important factor affecting the vehicle off-road maneuver. High-precision rainfall data is a prerequisite for evaluating battlefield off-road traffic capacity quantitatively and developing a program of action reasonably. In view of the shortcomings of traditional interpolation methods, the flitersim multi-point statistical method is used to improve the fusion accuracy of multi-source precipitation data. The rainfall is decomposed into the sum of the local mean and the local residual, the local residuals of the satellite precipitation data are used as the "training data", the local residual data of the weather stations are used as the "hard data", and the interpolation data of the local residual data of the satellite precipitation and the local residual data of the weather station are used as the "soft data" for flitersim multi-point statistical simulation to obtain 1 km resolution precipitation data. By comparing the average absolute error, the root mean square error and the correlation coefficient of several sets of data, it is shown that flitersim is superior to the ordinary cooperative kriging interpolation, which can improve the accuracy of precipitation data effectively.

Key words: precipitation data fusion, multi-point statistics, hard data, soft data