信息融合技术是一个多学科高度集成的热点研究领域,目前针对煤矿井下环境监测系统的安全隐患问题,提出了一种基于无线传感器网络的分布递阶卡尔曼滤波信息融合算法,其中下层源节点采用改进卡尔曼滤波算法,上层汇聚节点采用方差自适应的加权信息融合算法,该算法能有效降低无线传感器网络能耗和网络信息冲突,实现信号重构.仿真结果表明,该算法具有很高的可靠性和信息融合精度,有较好的工程实用价值.
Information fusion technology is a multidisciplinary highly integrated popular research fields. In view of the security threats in the coal mine environmental monitoring system, A distributed hierarchical information fusion algo- rithm is proposed in wireless sensor network. In the source, the inproved Kalman filtering are used to reduce the power consumption and data collision. In the sink, the dynamic weighted fusion algorithm based on linear minimum variance sense is adopted. This method is minimize the overall power consumption and the probability of collision in the network as well, it can realize signal reconstruction. A simple example is performed to verify the reliability and fusioning pre- cision of this method, at the same time it has high fault-tolerant.