改进贝叶斯滤波模型井下人员定位算法的研究

Improved Location Algorithm of Workers under Coal Mines Based on Bayesian Filtration Model

研究矿井采矿过程监控问题,由于矿井自身的局限性和环境参数的复杂性,无线传感器网络节点定位技术被广泛应用在矿井作业过程中。为确保通信数据的可靠性和有效性,保证提高定位精度,提出多通道传输数据机制,实现对数据信息进行实时有效的采集。通过对传统定位算法原理和误差来源进行分析,结合贝叶斯滤波概率模型对Euclidean定位算法进行改进,使接收信号强度指示器随机波动得到有效的抑制。通过对节点之间坐标区域范围的修正,使信号强度最终达到平衡。实验证明,提高了可靠性,改进后算法具有更高的定位精度,表明算法的有效性和正确性。

Because of the limitation of coal mines and complexity of environmental parameters,nodes location of wireless sensor network（WSN） is widely used in borehole operation.In order to guarantee the reliability and validity of communication data,multi-channel data transmission system was proposed for real-time and effective collection of data.Then the principle and error of traditional location algorithm was analyzed and Euclidean location algorithm was improved combined with Bayesian filtration.Random fluctuation of Received Signal Strength Indicator（RSSI） was effectively controlled.Through revision of the area among nodes on coordinator,the density of signals reached balance.What＇s more,the location accuracy was enhanced.Higher location accuracy of nodes was achieved.Experiment results demonstrate higher location accuracy,validity and correctness of the improved algorithm.