Fingerprint- And kalman filter-based localization exploiting reference signal received power calibration

被引：0
|
作者：
Eom C. [1 ]
Jung S. [1 ]
Im C. [1 ]
Lee C. [1 ]
机构：
[1] School of Electrical and Electronic Engineering, Yonsei University, Seoul
来源：
IEIE Transactions on Smart Processing and Computing | 2020年 / 9卷 / 03期
基金：
新加坡国家研究基金会;
关键词：
Fingerprint-based; Indoor environment; Kalman filter; Localization; RSRP-based;
D O I：
10.5573/IEIESPC.2020.9.3.238
中图分类号：
学科分类号：
摘要：
This paper proposes a localization scheme exploiting reference signal received power (RSRP) for estimation of the next location. The proposed scheme can correct outliers without discarding data by adding RSRP as a state vector for a Kalman filter, and combining the Kalman filter with fingerprint-based localization. Performance evaluation is carried out via simulations in indoor environments. Results indicate that the proposed scheme can effectively correct outliers and enhance positioning accuracy. The root mean square error in the positioning error was reduced by 56%, compared to the conventional fingerprint-based localization schemes for indoor environments. © 2020 Institute of Electronics and Information Engineers. All rights reserved.
引用
收藏
页码：238 / 243
页数：5
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