基于Chan与AUKF联合的人员定位算法

Person location algorithm based on combination of Chan and AUKF

针对目前超宽带人员定位技术在复杂环境中产生较大误差的问题,提出了一种基于Chan算法与自适应无迹卡尔曼滤波AUKF的联合定位算法。利用Chan算法去除噪声较大的数据,确定误差相对较小的初始坐标,将Chan算法的估计值作为AUKF的初始值进行滤波处理,确定精确的位置坐标,在视距与非视距环境下仿真分析变电站的人员定位。结果表明,在视距环境下,文中提出的算法略优于Chan算法。在非视距环境下,Chan-AUKF联合定位算法的误差值约为10 cm,而Chan算法的误差值约为20 cm,定位精度提高约10 cm。

This paper is aiming at solving the problem that the current ultra-wideband personnel positioning technology exists large errors in complex environment,and proposing a joint positioning algorithm based on Chan algorithm and adaptive unscented Kalman filter.The study involves removing noisy data with Chan algorithm;determining the initial coordinates with relatively small error;filtering the estimated value of Chan algorithm as the initial value of AUKF;determining the accurate position coordinates,and simulating and analyzing the personnel positioning of substation in line-of-sight and non-line-of-sight environments.The results show that the algorithm proposed below is slightly better than Chan′s algorithm in line-of-sight environment;and in the non-line-of-sight environment,the error value of Chan-AUKF joint positioning algorithm is about 10 cm,while the error value of Chan algorithm is about 20 cm,which shows about 10 cm improvement of the positioning accuracy.