应用长短期记忆网络提高室内定位精度。

Application of LSTM Network to Improve Indoor Positioning Accuracy.

作者信息

Gao Dongqi, Zeng Xiangye, Wang Jingyi, Su Yanmang

机构信息

Hebei Key Laboratory of Advanced Laser Technology and Equipment, School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China.

Tianjin Key Laboratory of Electronic Materials and Devices, School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China.

出版信息

Sensors (Basel). 2020 Oct 15;20(20):5824. doi: 10.3390/s20205824.

DOI:10.3390/s20205824

PMID:33076259

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7602445/

Abstract

Various indoor positioning methods have been developed to solve the "last mile on Earth". Ultra-wideband positioning technology stands out among all indoor positioning methods due to its unique communication mechanism and has a broad application prospect. Under non-line-of-sight (NLOS) conditions, the accuracy of this positioning method is greatly affected. Unlike traditional inspection and rejection of NLOS signals, all base stations are involved in positioning to improve positioning accuracy. In this paper, a Long Short-Term Memory (LSTM) network is used while maximizing the use of positioning equipment. The LSTM network is applied to process the raw Channel Impulse Response (CIR) to calculate the ranging error, and combined with the improved positioning algorithm to improve the positioning accuracy. It has been verified that the accuracy of the predicted ranging error is up to centimeter level. Using this prediction for the positioning algorithm, the average positioning accuracy improved by about 62%.

摘要

为解决“地球上的最后一公里”问题，人们开发了多种室内定位方法。超宽带定位技术因其独特的通信机制在所有室内定位方法中脱颖而出，具有广阔的应用前景。在非视距（NLOS）条件下，这种定位方法的精度会受到很大影响。与传统的检测和拒绝NLOS信号不同，所有基站都参与定位以提高定位精度。本文在充分利用定位设备的同时，使用了长短期记忆（LSTM）网络。LSTM网络用于处理原始信道冲激响应（CIR）以计算测距误差，并结合改进的定位算法提高定位精度。经验证，预测测距误差的精度可达厘米级。将此预测应用于定位算法，平均定位精度提高了约62%。