基于信道模糊关联识别的NLOS测距误差补偿算法

doi:10.13190/j.jbupt.2019-084

北京邮电大学学报 ›› 2020, Vol. 43 ›› Issue (1): 21-27.doi: 10.13190/j.jbupt.2019-084

基于信道模糊关联识别的NLOS测距误差补偿算法

李晓辉^1,2, 杜洋帆², 石潇竹¹, 杨胥²

1. 中国电子科技集团公司第二十八研究所空中交通管理系统与技术国家重点实验室, 南京 210007;
2. 西安电子科技大学综合业务网理论及关键技术国家重点实验室, 西安 710071

收稿日期:2019-05-20 出版日期:2020-02-28 发布日期:2020-03-27
作者简介:李晓辉(1972-),女,教授,博士生导师,E-mail:xhli@mail.xidian.edu.cn.
基金资助:
国家重点研发计划项目（2018YFB1802004）；空中交通管理系统与技术国家重点实验室开放基金项目（SKLATM201807）；高等学校学科创新引智计划项目（B08038）

NLOS Ranging Error Compensation Algorithm Based on Fuzzy Association Channel Identification

LI Xiao-hui^1,2, DU Yang-fan², SHI Xiao-zhu¹, YANG Xu²

1. State Key Laboratory of Air Traffic Management System and Technology, The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, China;
2. State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710071, China

Received:2019-05-20 Online:2020-02-28 Published:2020-03-27
Supported by:

摘要/Abstract

摘要： 针对NLOS测距存在误差的问题，提出一种基于信道模糊关联识别的NLOS测距误差补偿算法.根据先验信道特征参数分布信息构造信道特征参数模糊隶属矩阵，并利用灰色关联分析方法计算归一化权值矩阵，进而获得模糊综合评价矩阵来对信道环境进行识别.在此基础上，根据信道识别结果构建Huber代价函数，通过Huber线性回归方法对原始测距结果进行迭代重构，将重构结果作为Kalman滤波的测量值进行滤波.仿真结果表明，所提算法可以有效提高NLOS环境下的测距精度，在信噪比大于-2 dB时可以达到厘米级测距精度.

关键词: 非视距, 信道识别, 模糊综合评判, Huber线性回归

Abstract: Aiming at the problem of ranging errors in non line of sight (NLOS) ranging, an NLOS ranging error compensation algorithm is proposed based on fuzzy association channel identification. The algorithm constructs fuzzy membership matrix of channel feature parameters based on the prior channel feature parameter distribution information, and uses gray correlation analysis method to calculate the normalized weight matrix, so that to obtain the fuzzy comprehensive evaluation matrix to identify the channel environment. On this basis, the Huber residual cost function is constructed according to the channel identification result, and the original ranging result is iteratively reconstructed by Huber linear regression method, which is filtered as the measured value of Kalman filter. Simulation show that the proposed algorithm can improve the ranging accuracy under NLOS effectively, and the range accuracy of this algorithm can reach centimeter level when signal-to-noise ratio is -2 dB.

Key words: non line of sight, channel identification, fuzzy comprehensive evaluation, Huber linear regression

中图分类号:

TN929.53

李晓辉, 杜洋帆, 石潇竹, 杨胥. 基于信道模糊关联识别的NLOS测距误差补偿算法[J]. 北京邮电大学学报, 2020, 43(1): 21-27.

LI Xiao-hui, DU Yang-fan, SHI Xiao-zhu, YANG Xu. NLOS Ranging Error Compensation Algorithm Based on Fuzzy Association Channel Identification[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(1): 21-27.

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基于信道模糊关联识别的NLOS测距误差补偿算法

NLOS Ranging Error Compensation Algorithm Based on Fuzzy Association Channel Identification

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