【摘要】 为解决移动机器人在非视距(non-line of sight, NLOS)环境下定位系统误差大和稳定性差的问题,提出一种抗NLOS误差的N-CTK(NLOS Chan-Taylor-Kalman)组合算法。首先在Chan-Taylor协同算法基础上,融入卡尔曼滤波算法,提出一种CTK组合定位算法,然后基于TDOA(time difference of arrival)测量值构建NLOS误差模型,引入NLOS误差转化因子,融合扩展卡尔曼滤波算法,并结合所提CTK组合算法,最终获得标签的估计值。实验测试表明:视距(line of sight, LOS)环境下误差为6 cm时,N-CTK组合算法相比CTK组合算法的累积分布函数提高了13.5%, NLOS环境下误差为15 cm时,N-CTK组合算法相比CTK组合算法的累积分布函数提高了55%,定位精度明显提高。更多还原

【Abstract】 In order to solve the problem of large error and poor stability of mobile robot positioning system in non-line of sight(NLOS) environment, a novel NLOS error resistant NLOS Chan-Taylor-Kalman(N-CTK) combined algorithm was proposed. Firstly, based on the Chan-Taylor collaborative algorithm, a CTK combined positioning algorithm was proposed by integrating the Kalman filter algorithm. Then, the NLOS error model was built based on the TDOA(time difference of arrival) measurement value, the NLOS error conversion factor was introduced, the extended Kalman filter algorithm was fused, and the proposed CTK combined algorithm was combined to obtain the estimated value of the tag finally. Experimental results show that the cumulative distribution function of the N-CTK algorithm is 13.5% higher than that of the CTK algorithm when the error is 6 cm in line of sight LOS environment, and 55% higher than that of the CTK algorithm when the error is 15 cm in NLOS environment, and the positioning accuracy is significantly improved.更多还原