Wi-Fi信号下室内目标位置无监督定位算法研究  

Research on Unsupervised Localization Algorithm of Indoor Target Position under Wi-Fi Signal

作　　者：胡博[1] 钱鑫[2] HU Bo;QIANG Xin(Information Construction and Management Center,Nanjing Normal University of Special Education,Nanjing Jiangsu 210038,China;Nanjing University of Aeronautics and Astronautics,Nanjing Jiangsu 210007,China)

机构地区：[1]南京特殊教育师范学院,江苏南京210038 [2]南京航空航天大学,江苏南京210007

出　　处：《计算机仿真》2024年第6期435-440,共6页Computer Simulation

摘　　要：单一定位算法存在精确性低与稳定性差的问题,直接应该目标轨迹定位结果。为解决上述问题,在95m×30m的实验环境中采用移动传感器(方向传感器、三轴加速度器与线性加速度)进行数据采集,通过将改进Wi-Fi定位算法与PDR优化算法与KEF算法进行有机融合,构建出EPW目标轨迹定位算法。算法首先对传统Wi-Fi定位算法进行改进,基于AP信号损失分析结果,采用无监督KNN算法优化Wi-Fi定位算法,降低定位的波动性,提高定位的精确性;然后采用阈值峰谷法检测步频,并通过对地转换优化航向角估计,降低了传统PDR算法的累计误差量;最终基于KEF算法对改进的Wi-Fi定位算法与PDR优化定位算法采集的非线性数据进行拟合融合,解决单一算法的短板问题,大幅度提升了定位系统的鲁棒性。EPW算法仿真结果表明,在高斯噪声的标准差为4.0dBm时,EPW轨迹定位算法与实际轨迹偏离程度最小,在轨迹拐弯处仍能保持较好的连续跟随性,其均方根误差仅为0.97m;算法对比仿真结果显示,较其它六类定位算法相比,EPW算法的ME、RMSE与MAX误差分别平均降低了2.82m、1.76m和4.34m,表明EPW定位算法具有最高的精确性、稳定性与鲁棒性。综上所述,EPW轨迹定位算法解决了单一算法的缺陷,提高了定位的精确度与稳定性,具有极高的仿真价值。The single localization algorithm has the problems of low accuracy and poor stability,and the localiza⁃tion result of the target trajectory should be obtained directly.In order to solve the above problems,this paper uses mobile sensors(direction sensor,three-axis accelerometer and linear acceleration)to collect data in a 95m×30m ex⁃perimental environment,and constructs an EPW target trajectory positioning algorithm by integrating the improved Wi-Fi positioning algorithm with PDR optimization algorithm and KEF algorithm.Firstly,the algorithm improves the tra⁃ditional Wi-Fi positioning algorithm,and uses KNN to optimize the Wi-Fi positioning algorithm based on the analysis results of AP signal loss,which reduces the fluctuation of positioning and improves the accuracy of positioning;then it uses the threshold peak-valley method to detect the step frequency,and optimizes the heading angle estimation through ground conversion,which reduces the cumulative error of the traditional PDR algorithm.Finally,the nonlinear data collected by the improved Wi-Fi positioning algorithm and the PDR optimization positioning algorithm are fitted and fused based on the KEF algorithm,which solves the short board problem of a single algorithm and greatly im⁃proves the robustness of the positioning system.The simulation results show that when the standard deviation of Gaussian noise is 4.0 dBm,the EPW trajectory localization algorithm has the minimum deviation from the actual traj⁃ectory,and can still maintain good continuous tracking performance at the corner of the trajectory,with a root mean square error of only 0.97m.The simulation results show that the MEE,RMSE and MAX errors of the EPW algorithm are reduced by 2.82 m,1.76 m and 4.34 m,respectively,compared with the other six algorithms,which indicates that the EPW algorithm has the highest accuracy,stability and robustness.To sum up,the EPW trajectory positioning algo⁃rithm solves the defects of a single algorithm,improves the accuracy and stability of positioning,and

关 键 词：定位 扩展卡尔曼滤波 优化 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]