The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monitoring point,and that is to say it can only handle one-dimensional time series.Given this shortage in the monitoring, the multi-sensor information fusion in the state estimation techniques would be intro- duced to the slope deformation monitoring system,and by the dynamic characteristics of deformation slope,the open pit slope would be regarded as a dynamic goal,the condi- tion monitoring of which would be regarded as a dynamic target tracking.Distributed In- formation fusion technology with feedback was used to process the monitoring data and on this basis Klman filtering algorithms was introduced,and the simulation examples was used to prove its effectivenes. The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monitoring point, and that is to say it can only handle one-one time series.Given this shortage in the monitoring, the multi-sensor information fusion in the state estimation techniques would be intro- duced to slope deformation monitoring system, and by the dynamic characteristics of deformation slope, the open pit slope would be ideal as a dynamic goal, the condi- tion monitoring of which would be considered as a dynamic target tracking. Distributed In-formation fusion technology with feedback was used to process the monitoring data and on this basis Klman filtering algorithms was introduced, and the simulation examples was used to prove its effectivenes.