基于聚类分析优化的距离修正室内定位算法

基于接收信号强度RSSI的定位系统易受环境影响,提出一种基于聚类算法分析的高斯混合滤波的RSSI信号处理优化策略,通过优化接收信号强度及距离修正的四边质心定位算法对未知节点进行精确室内定位,使用蓝牙4.0信标节点进行实地实验。实验结果表明,该算法可以有效提高测距精度,改善系统的定位精度,比传统加权质心算法的定位精度提高了34.6%,且定位平均误差不超过0.5m,可满足室内定位精度要求。

Distance rectification indoor localization based on cluster analysis optimization

The localization system based on received signal strength indication (RSSI) is vulnerable to environmental impact, we therefore present a RSSI signal processing optimization strategy based on clustering analysis of the Gaussian mixture model. We achieve accurate indoor localization of unknown nodes through the optimization of the RSSI and the distance rectification of the four sides centroid localization algorithm. Experiments on Bluetooth 4.0 beacon nodes validate that the algorithm can effectively improve range accuracy and location precision. The location precision is increased by 34.6% than the conventional weighted centroid algorithm, and the average error of localization is less than 0.5 m, which meets the location precision requirement.