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无线精确定位被广泛应用于矿山物联网技术领域,针对煤矿巷道定位算法普遍存在定位精度不高、误差大、易受环境干扰、被定位目标抖动和漂移等问题,提出一种基于高斯滤波的分段实时计算动态路径损耗因子α和环境参量ε_σ的接收信号强度指标(RSSI)高精度巷道定位算法.实验中采用加权最小二乘法和最小二乘法曲线拟合方法,实时动态计算路径损耗因子和环境参量来构建符合煤矿井下特殊环境的信号传输模型;在位置坐标求解阶段引入距离误差修正参数Δμ,采用标准最小均方差迭代估计出未知节点的位置坐标.以锚节点不同布置方案对算法进行实地测距验证.结果表明:提出的算法定位平均精度为1.6m,最坏情况是2.8m,横向平均误差为1.2m,纵向平均误差为0.8m;相比固定路径损耗因子的RSSI算法提高了定位精度,降低了误差率.
Precise wireless location is widely used in the field of mine networking technology. Aiming at the problems such as poor positioning accuracy, large error, easily disturbed by the environment and jitter and drift of the target, coal mine tunnel location algorithm generally presents a new algorithm based on Gaussian filter Section real-time calculation of RSSI (RSSI) dynamic path loss factor α and environmental parameter εσ.A weighted least squares method and a least squares curve fitting method are used to calculate the path loss factor and the environment in real time Parameters to construct a signal transmission model in line with the special underground coal mine environment; the distance error correction parameter Δμ is introduced in the position coordinate solving stage, and the position coordinates of unknown nodes are estimated by standard minimum mean square error iteration. The results show that the proposed algorithm has an average positioning accuracy of 1.6m, a worst case of 2.8m, a horizontal average error of 1.2m and a longitudinal average error of 0.8m. Compared with the fixed path loss factor, the RSSI algorithm improves the positioning accuracy , Reducing the error rate.