基于修正 RSSI 值的四边形加权质心定位算法

在利用接收信号强度指示(RSSI)对无线传感器网络中的未知节点进行定位时,RSSI 值易受环境的影响导致定位误差, 为此提出基于 RSSI 测距修正的四边形加权质心定位算法(QWCRC)。 先对来自同一锚节点的多个 RSSI 值进行卡尔曼滤波,得 到修正的 RSSI 值,致使测距尽可能的接近真实距离;再采用四边形加权定位对未知节点进行定位,同时利用最小二乘法进行辅 助定位,此算法对于相邻锚节点圆不相交的情况给出新的解决方案。 实验结果对比表明,改进的算法相比较于四边形加权质心 算法(QWC)和 RSSI 测距修正的三角形加权算法(TWCRC),在锚节点数目 5×5 和噪声强度为 0 dbm 时,定位精度可分别提升 87. 14%和 35. 51%。

Quadrilateral weighted centroid localization algorithm based on RSSI of correction

When RSSI is used to locate unknown node of wireless sensor network, the RSSI values are easily affected by environment will cause location error. Thus, quadrilateral weighted centroid localization algorithm based on range correction of RSSI ( QWCRC) is proposed. Firstly, the optimized RSSI value is obtained by Kalman filtering of the received RSSI values, which makes the ranging as close as possible to the real distance. Secondly, location of unknown node is determined by quadrilateral weighted centroid localization algorithm, at the same time, the method of least squares is used for auxiliary positioning. A new solution is provided by the algorithm to the case where the adjacent anchor node circle does not intersect. Finally, the experimental results show that compared with the quadrilateral weighted centroid algorithm ( QWC) and the triangle weighted algorithm modified by RSSI ranging ( TWCRC), the positioning accuracy of the improved algorithm can be improved by 87. 14% and 35. 51% respectively when the number of anchor nodes is 5×5 and the noise intensity is 0 dbm.