煤矿井下基于RSSI的多维标度定位算法

    Multidimensional Scaling Positioning Algorithm Based on RSSI in Underground Coal Mine

    • 摘要: 针对煤矿井下环境复杂多变,受限无线信道容易受到非视距、多径衰落及人为因素的影响,导致指纹匹配技术定位算法误差较大,提出了一种基于RSSI的多维标度定位算法。该算法根据井下巷道信号传播模型测距构建相异性矩阵,利用多维标度法计算节点相对坐标,通过平面四参数模型转换为移动节点的绝对坐标,引入粒子群算法优化节点位置坐标,实现对井下移动目标的实时定位。对比试验表明,优化后的节点定位精度有了明显的提高,满足低成本定位系统的需求。

       

      Abstract: The coal mine environment is complex and changing, radio channel is easily affected by non-line of sight, multipath fading, and human factors, so location error of RSSI-based fingerprint positioning technology is large; we proposed a multidimensional scaling positioning algorithm based on RSSI. In this paper, we construct the dissimilarity matrix according to the ranging of coal mine signal propagation model; MDS method is used to calculate the relative coordinates of the nodes. According to the planar four parameters model, we can calculate real coordinates of the mobile nodes; the particle swarm optimization is used to optimize the position coordinates of the nodes. This method can realize the moving target location in the coal mines in real time. Experiments show that, after optimization, the positioning accuracy of node is improved obviously. It meets the needs of low cost in the positioning system.

       

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