Abstract:

Aiming at the problems of low positioning accuracy and poor stability in multi?effect and non?line?of?sight conditions, a new indoor positioning system Chan?Taylor?Unscented Kalman Filter (C?T?UKF) combined positioning algorithm is designed based on the time of flight positioning algorithm, combined with the Chan?Taylor (C?T) cooperative positioning algorithm, and fused with the Unscented Kalman Filter (UKF) algorithm. The system mainly consists of positioning base stations, positioning tags, wireless communication systems and upper computers, etc. The Chan algorithm is adopted to calculate the distance measured by the time of flight method, and the calculated coordinates are used as the initial value of the Taylor algorithm for iterative calculation. The iterative results are smoothed by the Unscented Kalman algorithm. The results show that the positioning system based on this algorithm has the characteristics of high accuracy, strong stability and low cost. The average positioning errors in line?of?sight and non?line?of?sight conditions are less than 0.17 m and 0.20 m respectively, and it can be applied to high?precision positioning scenarios.

Key words: Indoor positioning, Time of flight, Unscented kalman filter, Non?line of sight

摘要：

针对在多效应和非视距情况下定位精度低、稳定性差等问题，基于飞行时间定位算法，结合陈?泰勒（Chan?Taylor，C?T）协同定位算法，再融合无迹卡尔曼滤波（Unscented Kalman Filter，UKF）算法，设计了一种室内定位系统——陈?泰勒?无迹卡尔曼滤波（Chan?Taylor? Unscented Kalman Filter，C?T?UKF）组合定位算法。该系统主要由定位基站、定位标签、无线通信系统及上位机等组成；采用Chan算法，对通过飞行时间方法测出的距离进行解算，并将解出的坐标作为Taylor算法的初始值进行了迭代计算；通过UKF算法，对迭代的结果进行了平滑处理。结果表明，该算法定位系统精度高，稳定性强，成本低，在视距与非视距的平均定位误差分别小于0.17 m和0.20 m，能够适用于高精度定位场合。

关键词: 室内定位, 飞行时间, 无迹卡尔曼滤波, 非视距