基于TOF和自适应抗差卡尔曼滤波的UWB室内定位算法

UWB indoor positioning algorithm based on TOF and adaptive robust KF

为提高超宽带(UWB)定位系统在室内复杂环境下的定位精度,提出一种基于飞行时间(TOF)和自适应抗差卡尔曼滤波(ARKF)的改进定位算法。针对超低功耗宽带设备在复杂室内环境状态下易受周围干扰而存在标准时间偏差的问题,提出一种改进的TOF算法,同时进行测距标定,拟合数据;对室内存在非视距(NLOS)干扰的情形,提出一种ARKF算法,通过比较残差与3倍信息的方差来判断视距(LOS)与NLOS情形。实验结果显示:该算法可以在静态与动态定位实验中有效提高系统定位精度,降低定位误差,取得较好的定位效果。

In order to improve the positioning precision of ultra-wideband(UWB)positioning system in indoor complex environment,an improved positioning algorithm based on time of flight(TOF)and adaptive robust Kalman filtering(ARKF)is proposed.Aiming at the standard time deviation of ultra-low power consumption broad band devices that are susceptible to surrounding interference in complex indoor environments,an improved TOF algorithm is proposed,and the ranging calibration is carried out at the same time to fit the data.For the case of non-line-of-sight(NLOS)interference indoor,an ARKF algorithm is proposed,which judges the sight distance and NLOS situation by comparing the residual with the variance of 3 times the information.Experimental results show that the algorithm can effectively improve the positioning precision of the system,reduce the positioning error,and achieve better positioning effect in static and dynamic positioning experiments.