基于卡尔曼滤波的加权补偿定位算法

发布时间：2018-03-19 08:30

  本文选题：无线传感器网络　切入点：RSSI测距　出处：《计算机工程与设计》2017年10期 　论文类型：期刊论文

【摘要】：针对WSN定位算法在测距和定位过程中存在较大误差的问题,提出基于Kalman滤波的加权补偿定位算法。利用Kalman滤波模型对RSSI信号值进行平滑处理,使接收到的信号强度值更趋近于真实值;选取相邻锚节点与待测节点之间距离倒数的和作为权值因子,并用它们之间的距离比对权值因子进行优化,采用二次加权质心算法计算待测节点的位置;再定位周边的锚节点得出误差均值,对待测节点的位置加以补偿。仿真结果表明,所提算法的定位精度比基于RSSI的加权质心算法提高了5%-6%。
[Abstract]:In order to solve the problem of large error in WSN location algorithm, a weighted compensation localization algorithm based on Kalman filter is proposed. The RSSI signal value is smoothed by Kalman filter model. The received signal intensity value is closer to the real value, the reciprocal sum of the distance between adjacent anchor node and the node to be tested is selected as the weight factor, and the weight factor is optimized by the distance ratio between them. The quadratic weighted centroid algorithm is used to calculate the position of the node to be tested, the error mean value is obtained by locating the surrounding anchor node, and the position of the measured node is compensated. The simulation results show that, Compared with the weighted centroid algorithm based on RSSI, the accuracy of the proposed algorithm is improved by 5-6.
【作者单位】： 沈阳航空航天大学计算机学院;
【基金】：航空科学基金项目(2014ZC54012) 辽宁省自然科学基金项目(2013024002) 辽宁省教育厅基金项目(L2013063)
【分类号】：TN929.5;TP212.9
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本文编号：1633466