基于多层神经网络的超宽带室内精确定位算法

›› 2014, Vol. 27 ›› Issue (5): 161-.

基于多层神经网络的超宽带室内精确定位算法

沈冬冬,李晓伟,宋旭文,贺志楠

(西安电子科技大学电子工程学院,中国西安 710071)

出版日期:2014-05-15 发布日期:2014-05-14
作者简介:沈冬冬(1988—),男,硕士研究生。研究方向:无线传感网,嵌入式。E-mail:dongdongqyr@126.com

UWB Indoor Precise Positioning Algorithm Based on Multilayer Neural Network

SHEN Dongdong,LI Xiaowei,SONG Xuwen,HE Zhinan

(School of Electronic Engineering,Xidian University,Xi'an 710071,China)

Online:2014-05-15 Published:2014-05-14

摘要/Abstract

摘要：

选定 IEEE802.15 信道模型工作小组提出的IEEE802.15.4a模型作为超宽带室内定位的普遍适用模型。在研究了传统室内定位算法的基础上,利用多层神经网络技术,对到达时间差和到达角度混合算法进行改进,并做了仿真分析。仿真结果显示,定位精度明显提高,效果理想。

关键词: 超宽带, 信道模型, 室内定位, 多层神经网络, TDOA, AOA

Abstract:

This paper selects the IEEE802.15 channel model proposed by IEEE802.15 channel model working group for the UWB indoor positioning.The time difference of arrival (TDOA) and angle of arrival (AOA) hybrid algorithm improved by utilizing multi-layer neural network technology based on the study of the conventional indoor positioning algorithm.The positioning accuracy is analyzed by simulation.The simulation results show the positioning accuracy is considerably improved.

Key words: UWB;channel model;indoor localization;multi-layer neural network;TDOA;AOA

中图分类号:

TN92

沈冬冬,李晓伟,宋旭文,贺志楠. 基于多层神经网络的超宽带室内精确定位算法[J]. , 2014, 27(5): 161-.

SHEN Dongdong,LI Xiaowei,SONG Xuwen,HE Zhinan. UWB Indoor Precise Positioning Algorithm Based on Multilayer Neural Network[J]. , 2014, 27(5): 161-.

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