20 March 1998 Data fusion system architecture for unattended ground sensors
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Abstract
In this paper, it develops an artificial intelligence method that uses object-oriented approach to construct the blackboard of data fusion for unattended 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 the 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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Junliang Zhang, Yuming Zhao, "Data fusion system architecture for unattended ground sensors", Proc. SPIE 3376, Sensor Fusion: Architectures, Algorithms, and Applications II, (20 March 1998); doi: 10.1117/12.303688; https://doi.org/10.1117/12.303688
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