3D-RABLC:一种基于LQI置信度的三维空间定位求精算法

3D-RABLC: a novel refinement algorithm based on LQI confidence for three-dimensional localization

提出一种基于LQI置信度的三维空间定位求精算法(3D-RABLC)。通过大量节点实验,获得节点间一跳RSSI值与距离的关系、LQI与分组错误率的关系,依此划分LQI置信度,对测得的RSSI值进行过滤,建立三维多跳求精模型或弥补求精方法对置信度低的RSSI值进行修正。节点实验表明,该算法大大降低了RSSI测距误差,比已有三维定位算法具有更好的定位精度。

A novel refinement algorithm based on LQI confidence for three-dimensional localization （3D-RABLC） was proposed. LQI confidence was obtained in terms of the relationships between RSSI and one hop distance, LQI and packet error rate （PER）, which derived from experimental data. The measured RSSI was filtered by LQI confidence. Moreover, the RSSI with lower confidence was modified by a three-dimensional multi-hop model or a compensating refinement method. The experiment results show that the algorithm reduces the RSSI range error, and improves the accuracy of three-dimensional localization significantly.