非视距环境下基于改进卡尔曼滤波器的LLOP-Taylor定位方法  

LLOP-Taylor Positioning Method Based on Modified Kalman Filter in NLOS Environment

作　　者：鲁兴 齐新力 张来洪 刘培杰 LU Xing;QI Xinli;ZHANG Laihong;LIU Peijie(Wuhan Zhongyuan Electronics Group Co.,Ltd.,Wuhan Hubei 430205,China;Henan University of Technology,Zhengzhou Henan 450001,China)

机构地区：[1]武汉中原电子集团有限公司,湖北武汉430205 [2]河南工业大学,河南郑州450001

出　　处：《通信技术》2023年第8期937-943,共7页Communications Technology

摘　　要：在无线通信定位中,无线信号中引入的非视距(Non-Line of Sight,NLOS)误差会严重降低系统的定位精度。针对上述问题,首先引入信息阈值和缩放因子,细分非视距误差的影响程度,对卡尔曼迭代过程中的增益进行更为精准的实时调整,利用改进后的卡尔曼滤波算法更大程度上消除了NLOS误差和系统测量误差;其次引入基于测距残差的加权系数对线性位置线(Linear Line of Position,LLOP)和Taylor定位方法的计算结果进行综合处理,进一步提高定位精度和稳健性。实验结果表明,在NLOS环境下,所提算法优于经典的LLOP算法、Chan算法、LLOP-Taylor算法和基于卡尔曼滤波的LLOP算法。In wireless communication positioning,the NLOS(Non-Line of Sight)errors introduced in wireless signals can seriously degrade the positioning accuracy of the system.To address the above problems,the information threshold and scaling factor are first introduced to subdivide the influence of NLOS error,and the gain in the Kalman iteration process is adjusted more accurately in real time,thus the modified Kalman filtering algorithm can eliminate NLOS error and systematic measurement error to a greater extent.Then,a weighting coefficient based on measurement residuals is introduced to comprehensively process the calculation results of LLOP(Linear Line of Position)and Taylor positioning methods,further improving the positioning accuracy and robustness.Experimental results indicate that the proposed algorithm is superior to the classical LLOP algorithm,Chan algorithm,LLOP-Taylor algorithm and Kalman filter-based LLOP algorithm in NLOS environment.

关 键 词：无线通信 非视距误差 卡尔曼滤波 加权系数 

分 类 号：TN929.5[电子电信—通信与信息系统]