Gaussian Filtered RSSI-based Indoor Localization in WLAN using Bootstrap Filter

被引:2
作者
Wang, Jingjing [1 ]
Hwang, Jun Gyu [1 ]
Peng, Jishen [1 ]
Park, Jaewoo [1 ]
Park, Joon Goo [1 ]
机构
[1] Kyungpook Natl Univ, Elect & Elect Engn, Daegu, South Korea
来源
2021 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 2021年
关键词
Indoor Positioning Algorithm; Received signal strength Indicator; Bootstrap Filter;
D O I
10.1109/CEIC51217.2021.9369804
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The ranging technology based on Received Signal Strength Index (RSSI) is widely used in Wireless Local Area Network (WLAN) positioning technology due to its low cost and low complexity. In the indoor positioning algorithm of RSSI positioning technology, due to the complexity of indoor environment and the randomness of personnel and other factors, it may be affected by noise, which needs to be suppressed. Based on the analysis and research of RSSI value, a processing algorithm of signal attenuation model combining Gaussian filter and Bootstrap filter is proposed. In the experiment, Gaussian filter is used to filter the abnormal RSSI value to get the optimal value, and then the nonlinear signal attenuation model is processed by Bootstrap filter algorithm. The experiment was carried out in a representative indoor environment and an anechoic chamber. Compared with the existing ranging algorithm based on average RSSI value, the algorithm can effectively remove the mutation data and noise fluctuation in RSSI value, realize the accurate smooth output of RSSI value and establish an accurate ranging model.
引用
收藏
页数:4
相关论文
共 45 条
[11]   Localization Based on RSSI Exploiting Gaussian and Averaging Filter in Wireless Sensor Network [J].
Ranjan Kumar Mahapatra ;
N. S. V. Shet .
Arabian Journal for Science and Engineering, 2018, 43 :4145-4159
[12]   Localization Based on RSSI Exploiting Gaussian and Averaging Filter in Wireless Sensor Network [J].
Mahapatra, Ranjan Kumar ;
Shet, N. S. V. .
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2018, 43 (08) :4145-4159
[13]   RSSI-Based Self-Localization with Perturbed Anchor Positions [J].
Kumar, Vikram ;
Arablouei, Reza ;
Jurdak, Raja ;
Kusy, Branislav ;
Bergmann, Neil W. .
2017 IEEE 28TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2017,
[14]   Adaptive RSSI-based localization scheme for wireless sensor networks [J].
Mardini, Wail ;
Khamayseh, Yaser ;
Almodawar, Abdalrhman Abdalkareem ;
Elmallah, Ehab .
PEER-TO-PEER NETWORKING AND APPLICATIONS, 2016, 9 (06) :991-1004
[15]   Adaptive RSSI-based localization scheme for wireless sensor networks [J].
Wail Mardini ;
Yaser Khamayseh ;
Abdalrhman Abdalkareem Almodawar ;
Ehab Elmallah .
Peer-to-Peer Networking and Applications, 2016, 9 :991-1004
[16]   RSSI-Based Localization of a Wireless Sensor Node with a Flying Robot [J].
Bohdanowicz, Frank ;
Frey, Hannes ;
Funke, Rafael ;
Mosen, Dominik ;
Neumann, Florentin ;
Stojmenovic, Ivan .
30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II, 2015, :708-715
[17]   Selected RSSI-based DV-Hop Localization for Wireless Sensor Networks [J].
Wongkhan, Mongkol ;
Chantaraskul, Soamsiri .
ENGINEERING JOURNAL-THAILAND, 2015, 19 (05) :199-212
[18]   RSSI-based Floor Localization Using Principal Component Analysis and Ensemble Extreme Learning Machine Technique [J].
Qi, Guowen ;
Jin, Yi ;
Yan, Jun .
2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2018,
[19]   3-D Indoor Localization and Identification Through RSSI-Based Angle of Arrival Estimation With Real Wi-Fi Signals [J].
Yen, Ho-Chun ;
Yang, Liang-Yu Ou ;
Tsai, Zuo-Min .
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (10) :4511-4527
[20]   The Study of Perpendicular Distance Approach Based on RSSI for Indoor Localization [J].
Abdelraouf, Ahmed ;
Ashour, Mohamed ;
Hammad, Hany F. ;
Elshabrawy, Tallal .
PROCEEDINGS OF 2019 INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN COMPUTER ENGINEERING (ITCE 2019), 2019, :208-213