基于质心-Taylor的UWB室内定位算法研究

Research of indoor location algorithm based on centroid-taylor

针对室内环境影响定位精度的非视距传播(non-line-of-sight,NLOS)问题,在对基于到达时间差(time differ-ence of arrival,TDOA)的超宽带(ultra wideband,UWB)室内定位模型和算法进行分析研究的基础上,提出了质心-Taylor混合定位算法。该算法利用对测距误差不敏感的质心算法对目标进行初始粗定位,然后将其作为Taylor级数展开法的迭代初值进行二次精细定位,并动态地将前期定位完毕的节点转化为后续定位过程的参考节点,最大限度地利用不断增加的已知信息,在提高Taylor初值质量的前提下减少预设参考节点数目,降低系统硬件成本。采用MATLAB软件进行了模拟仿真。仿真结果表明,该算法定位性能优越,尤其在NLOS测距误差较大的环境下能有效地提高系统的定位精度。

A novel Centroid-Taylor cooperative position scheme in NLOS environment is proposed by researching the indoor positioning models and algorithms of ultra wideband（UWB）. The Centroid algorithm that is not sensitive to location error is used for initial rough location, and then the value of the rough location is used as the initial value of Taylor algorithm for precise positioning. It inverts the nodes positioning completely into reference nodes. It can increase the quality of initial value for Taylor algorithm, also decrease the number of reference nodes in order to reduce system hardware costs. Simulation results show that this method has superior positioning performance, especially the great improvement of system under the large ranging error caused by NLOS.