基于UWB的SS-TWR改进方法研究与实现

针对卫星导航信号缺失或极易受扰的条件下,室内快速移动机器人与室外密集飞行的无人机集群必须依靠高精度高实时性相对定位实现运动导航与控制以及个体间避碰,亟需探索时间短、精度高的方法.对UWB测量体制深入研究后,提出时间可估算的单边双向测距(SS-TWR)的改进方法测距系统.系统建立了详细的序列时间分析与估算方法,与常用的双边双向测距(DS-TWR)相比,缩短了距离测量时间,提高了测量频率,减少了错误帧数量;采用有源温补晶振校正时钟,构建修正天线辐射近场区的误差经验模型,并引入卡尔曼滤波对测量结果进行融合估计,降低了测量误差;在室内环境的对比测试实验证明,改进后的SS-TWR精度达到与DS-TWR相当的±5 cm,测距时间小于5 ms.

Research and implementation of improved SS-TWR method based on UWB

Focusing on the dilemma that under the condition of satellite navigation signal void or extreme susceptibility to interference, indoor fast-moving robots and large-scale drone clusters flying outdoors must rely on high-precision and high-real-time relative positioning to achieve motion navigation and control so that to avoid collisions between each individual, it is urgent to further explore methods with high real-time performance and high accuracy. Based on the in-depth study of the UWB ranging system, this paper proposed an improved time-estimable single-sided two-way ranging(SS-TWR) method, and established a processing system for the process of "ranging request-radio frequency module transmission-antenna delay correction-reverse transmission of the received signal". First, the system established a detailed sequence time analysis and estimation method. compared with the commonly used double-sided two-way ranging(DS-TWR), it shortened the ranging time, increased the survey frequency, and decreased the number of error frames. Secondly, the system used an active temperature-compensation crystal oscillator to correct the clock, constructed an empirical model for correcting the error in the near-field area of the antenna radiation, and introduced the Kalman filter to conduct fusion estimation to the ranging results, which reduced the measurement error. Finally, through a comparative test experiment in an indoor environment, it verifies that the accuracy of the improved SS-TWR reaches±5 cm equivalent to that of the DS-TWR, and the ranging time is less than 5ms.