The data fusion system architecture for unattended ground sensors

In this paper,it develops an artificial intelligence method that uses object-oriented approach to construct the blackboard of data fusion for unattented ground sensors including geophone sensor, acoustic sensor, pressure sensor, infra-red sensor, magnetic sensor, image sensor etc.. It can perform detection, correlation, association and estimation to the sensors' output and obtain the exact recognition of targets, the number of target groups and the estimation for both the states of targets and the situation and threat. The whole blackboard is divided into three regions, including: single sensor fusion region, multisensor fusion region and threat estimation region. The three regions are expressed in classes. Knowledges of each domain in three regions are also expressed by classes and encapsulated in class hierarchy structure. Thus the whole blackboard can be viewed as object forest, the distributed knowledge inference can be realized by object reference. Both statistics and hierarchy inference approaches are used in the blackboard structure so as to efficiently perform fusion and inference. Furthermore,The method is realized in C++ language and demonstrated by the simulation of sensor alarming datum under battlefield environment.