基于Kalman滤波的Chan室内定位算法改进  

Modified Chan In-door Positioning Algorithm based on Kalman Filter

作　　者：仲江涛 秦斌[1,2] 吴健春 刘童 

机构地区：[1]深圳大学机电与控制工程学院,广东深圳518060 [2]深圳大学信息中心,广东深圳518060

出　　处：《通信技术》2017年第10期2223-2228,共6页Communications Technology

基　　金：赛尔网络下一代互联网技术创新项目(No.NGII20150308)~~

摘　　要：针对UWB(Ultra Wide Band)在室内定位中因环境复杂多变而导致的定位精度低问题,基于TDOA(Time Difference of Arrival)定位模型,提出了一种Chan-Kalman定位算法。Chan-Kalman定位算法结合卡尔曼滤波的思想,减少了在非视距和视距情况下因不确定性因素所造成的定位误差,即将Chan算法取得的估计值作为卡尔曼滤波算法的初始值,对位置进行二次估计。通过Matlab仿真平台,在测距误差|ε_d|≤10 cm的情况下,Chan-Kalman算法能将二维定位的均方根误差由RMS≤30 cm提高至RMS≤15cm。实验表明,Chan-Kalman定位算法能够有效减少定位误差,提高定位系统的精度和稳定性。Based on TDOA（Time Difference of Arrival） positioning model,Chan-Kalman positioning algorithm is proposed aiming at the problem that the positioning accuracy of UWB（Ultra Wide Band） is low due to the complex environment of UWB（Ultra Wide Band）.The Chan-Kalman positioning algorithm,in combination of Kalman filter idea,could reduce the positioning error caused by the uncertainty factor in the non-line-of-sight and the line-of-sight condition.The estimated value obtained by the Chan algorithm is taken as the initial value of the Kalman filter algorithm,and the position is estimated twice.Simulation with Matlab platform and in the case of ranging error at ±10 cm indicate that Chan-Kalman algorithm could reduce the two-dimensional positioning standard deviation from 30 cm to 15 cm.Experiment shows that Chan-Kalman positioning algorithm could effectively decrease the positioning error and improve the accuracy and stability of the positioning system.

关 键 词：室内定位 UWB TDOA CHAN算法 卡尔曼滤波 

分 类 号：TN923[电子电信—通信与信息系统] TN915.03[电子电信—信息与通信工程]