It is necessary to real-time and accurately monitor the position of people in mine for winning a safe production.However,considering the complex environment in the mine,wireless signal propagation in the mine will be affected by signal reflection,multipath propagation,noise,and so on,which results in low precision of traditional Wi-Fi positioning algorithm.To solve this problem,an improved way based on local maximum likelihood and the received signal strength is proposed to select the Wi-Fi signal nodes,and a hybrid algorithm about position that six point four and four combination is used.First,the beacon node periodically scans the mobile positioning module,and selects the optimum signal strength,the distance between the unknown node and the beacon node can be caculated.Then,the local maximum likelihood six point four and four combination is employed.Finally,the centroid algorithm is introduced to solve the problem of local center and estimate the final position of person in mine.The simulation results show that the positioning accuracy is improved significantly by the hybrid positioning algorithm.In the case of different noise and base station,several localization algorithms are analyzed and compared,the positioning accuracy of the new algorithm is still the best.Finally,the real-time performance of the proposed algorithm is analyzed.%实时精确监测井下人员位置,对安全生产非常必要.井下环境复杂、坑道狭长,不同于室内,一段坑道不会采集到太多较好信号节点,无线信号传播时易受反射、多径传播和噪声等因素影响,致使传统Wi-Fi定位算法定位精度低,提出一种基于局部极大似然、信号强度来遴选Wi-Fi信号节点,并利用六点四四组合混合定位算法.首先信标节点周期性扫描移动定位模块,筛选出较优信号强度,并求出待求节点与信标节点间距离;然后局部极大似然六点四四组合;最后质心法求解中心,估计最终的井下人员位置.经过仿真验证:所提出的混合定位算法,定位精度明显提高.同时分析了井下不同噪声、基站情况下,几种定位算法性能,新算法定位精度仍然较高;最后还分析了算法的实时性.
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