改进的Chan-Taylor联合定位算法

Improved Chan-Taylor Joint Localization Algorithm

针对超宽带(Ultra Wide Band,UWB)室内定位容易受到非视距(Non-Line of Sight,NLoS)误差干扰,导致室内定位精度下降的问题,提出了一种改进的Chan粒子滤波Taylor(Chan Particle Filter Taylor,CPFT)迭代定位算法,该算法通过Chan算法计算一个初始值,利用该初始值,结合粒子滤波算法对初始位置进行再次估计,将估计结果作为Taylor算法的初值。在Taylor算法每次迭代后,采用一维线性搜索算法,动态调整步长,更新估计位置,减小定位误差,防止其出现不收敛情况,最终输出定位坐标。实验结果表明,该算法可以有效抑制NLoS的影响,提高室内定位的精度。

Aiming at the problem that Ultra Wide Band(UWB)indoor localization is easily interfered by Non-Line of Sight(NLoS)errors,which leads to the degradation of indoor localization accuracy,an improved Chan Particle Filter Taylor(CPFT)iterative localization algorithm is proposed.It firstly calculates an initial value by the Chan algorithm and then utilizes this initial value,in combination with the particle filter algorithm,to estimate the initial position again.This estimated position is used as the initial value of the Taylor algorithm.Simultaneously,after each iteration of the Taylor algorithm,it adopts a one-dimensional linear search algorithm to dynamically adjust the step size,update the estimated position,reduce the localization error,and prevent non-convergence to output the localization coordinates finally.The experimental results show that the algorithm can effectively suppress the influence of NLoS and improve the accuracy of indoor localization.