Abstract：Time series of multi-sensor belong to non-stationary random process. Based on bootstrap of statistics and grey relational analysis of grey system theory，a method called BFGT(bootstrap fusion and grey testing) is proposed to resolve the problem about optimum fusion and its hypothesis testing for landslide time series of multi-sensor. By means of bootstrap resampling method and maximum entropy theory to imitate bootstrap distribution of time series of multi-sensor at different hours and in different positions，some of instantaneous features of the landslide process are depicted. Extracting these instantaneous features via calculation of the weighting mean using bootstrap distribution，bootstrap fusion series are formed. And grey rejection region of hypothesis testing for compatibility of time series of multi-sensor through definition of concepts，grey difference，attribute weight mapping and grey confidence level. By using time series information from distributed system of multi-sensor placed in different positions，the BFGT can simulate both transient state and evolvement process of overall landslide，which are described with maximum entropy probability distribution. In addition，by the aid of weighting mean value estimating technique of maximum entropy probability，the BFGT can identify probability distribution of the noise from information sources of multi-sensor at the same hour，reducing the noise，and then weakening influence of the noise on estimated results. Engineering application in landslide shows that the BFGT permits trend of non-stationary random process unknown and the number of data small without any requirements for probability distribution，having the lowest grey confidence level of 90% and the mean grey confidence level of 95%.
