| 基于RSSI和惯性导航的融合室内定位算法 |
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| 引用本文： | 朱亚萍,夏玮玮,章跃跃,燕锋,左旭舟,沈连丰.基于RSSI和惯性导航的融合室内定位算法[J].电信科学,2017,33(10):99-106. |
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| 作者姓名： | 朱亚萍 夏玮玮 章跃跃 燕锋 左旭舟 沈连丰 |
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| 作者单位： | 1. 东南大学移动通信国家重点实验室，江苏 南京 210096;2. 电子科技大学信息与软件工程学院，四川 成都 610054 |
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| 基金项目： | 国家自然科学基金资助项目(61471164;61601122)，中央高校基本科研业务费专项资金资助(KYLX16_ 0222)，网络与交换技术国家重点实验室(北京邮电大学)开放课题资助项目(No.SKLNST-2016-2-16)The National Natural Science Foundation of China(61471164;61601122)，Fundamental Research Funds for the Central University(KYLX16_0222)，Open Foundation of State Key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications)(SKLNST-2016-2-16) |
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| 摘 要： | 针对目前对高精度室内定位算法的需求，提出一种基于接收信号强度识别（RSSI）和惯性导航的融合室内定位算法。基于无线传感网中ZigBee节点的RSSI值，采用位置指纹识别算法，对网络中的未知节点进行定位。结合惯性传感单元（IMU）提供的惯性数据，对RSSI定位结果进行融合修正。利用Kalman滤波器，采用状态方程描述待定位节点位置坐标的动态变化规律，从而实现一种以无线传感网络定位为主、IMU为辅的融合定位方法。仿真结果表明，提出的融合定位算法既能改善单独使用RSSI定位受环境干扰较大的问题，又能避免单独使用惯性导航带来的累积误差，极大地提高了定位精度。
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| 关 键 词： | 高精度室内定位 接收信号强度识别 惯性导航 融合定位算法 |
A hybrid indoor localization algorithm based on RSSI and inertial navigation |
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| Yaping ZHU,Weiwei XIA,Yueyue ZHANG,Feng YAN,Xuzhou ZUO,Lianfeng SHEN.A hybrid indoor localization algorithm based on RSSI and inertial navigation[J].Telecommunications Science,2017,33(10):99-106. |
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| Authors: | Yaping ZHU Weiwei XIA Yueyue ZHANG Feng YAN Xuzhou ZUO Lianfeng SHEN |
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| Affiliation: | 1. National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China;2. University of Electronic Science and Technology of China,Chengdu 610054,China |
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| Abstract: | To cater for the requirements of high-precision indoor localization algorithms,a hybrid indoor localization algorithm based on received signal strength identification (RSSI) and inertial navigation was proposed.This algorithm used fingerprint identification algorithm to localize the agents,based on the RSSI values of ZigBee nodes in wireless sensor network.The algorithm combined the inertial information provided by inertial measurement units (IMU),to correct the RSSI localization results.This algorithm used Kalman filter and adopted state equations to describe the dynamic change rules of agents' positions,thus it achieved a hybrid localization algorithm which relied WSN localization first and IMU last.Simulations evaluate that the proposed algorithm can improve the localization performances of algorithms which adopt RSSI localization and inertial navigation individually,and can greatly improve localization accuracy. |
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| Keywords: | high-precision indoor localization received signal strength identification inertial navigation |
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