加权质心算法在Wi-Fi室内定位中的应用

Application of Weighted Centroid Algorithm on WIFI Indoor Positioning

目前基于信号强度的质心算法的定位精度,无法满足在固定的场景和区域中对高精度室内定位的要求,对此提出改进的加权质心算法进行Wi-Fi室内定位.采集的RSSI数据值波动较大,因此采用卡尔曼滤波方式对数据进行平滑处理,滤除异常值点.利用matlab对滤波后的RSSI值数据进行计算,分析数据值的分布密度与距离的关系.RSSI测距得出待测点到已设定3个锚节点的距离,以三个锚节点为圆心,通过测距得到的距离为半径画三个圆,得到3段圆弧相交的区域,通过以距离平方倒数之和作为权值,计算其3个交点连接成的三角形的质心坐标,最后以此三角形质心坐标作为初始值,再以信号强度之和作为权值,求解待测点坐标.实验结果表明,新坐标的定位精度相较原始坐标提高了95%左右.

As the positioning precision of centroid algorithm based on signal strength can’t meet the requirement for high accuracy indoor positioning in a fixed scene or area,the weighted centroid algorithm for the WIFI indoor positioning was put forward. Because the received RSSI data fluctuated greatly,Kalman filter was proposed to smooth the data processing and filter out outliers. After being filtered,RSSI data was calculated by using matlab,to analyze the relationship between the distribution density of data and distance. First,the distance between the test point and the three anchor nodes was obtained by RSSI ranging. With the distance as the radius and the three anchor nodes as the center of circle,three circles were drawn to get an area where the three arcs intersected.Second,with the square reciprocal sum of the distance as the weight,undertaken was the calculation of the barycentric coordinates of the triangle formed by connecting the three intersection points. Finally,with the triangle centroid coordinates as the initial value and the sum of the signal strength as the weights,the coordinates of the point to be measured were obtained. The results showed that the current positioning precision of the coordinates increases by about 95% compared with the original positioning precision.