Selecting anchor node based on RSSI ultra-wideband indoor positioning

被引:0
作者
Li, Bing [1 ,2 ]
Cui, Yi-Yang [1 ]
Liu, Yu [1 ]
Liu, Chun-Gang [1 ,3 ]
Gао, Zhan-Liang [4 ]
机构
[1] College of Combustion Engineering, Hebei Normal University, Shijiazhuang
[2] Hebei Provincial Innovation Center for Wireless Sensor Network Data Application Technology, Shijiazhuang
[3] Hebei Provincial Key Laboratory of Information Fusion and Intelligent Control, Shijiazhuang
[4] Hebei Pengbo Communication Equipment Co.,Ltd., Cangzhou
来源
Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 12期
关键词
anchor node selection; Cramér-Rao lower bound; indoor positioning; received signal strength indication; ultra-wideband; unsupervised;
D O I
10.13195/j.kzyjc.2024.0321
中图分类号
学科分类号
摘要
In ultra-wideband indoor positioning, due to the complex indoor environment, the communication between each anchor node and the positioning node will be subject to different degrees of interference, and the more interfered data will seriously affect the positioning accuracy, so it is necessary to screen the anchor nodes. Aiming at the above problems, an ultra-wideband indoor positioning anchor node selection method based on received signal strength indication (RSSI) is proposed. Firstly, the RSSI between the anchor nodes is calculated using the interpolation method and optimized by Gaussian process regression to obtain the initial RSSI estimation value. Secondly, this estimation value is Taylor-expanded at the anchor node position and the path loss factor to obtain the Fisher matrix with the RSSI information, and then, the Cramér-Rao lower bound (CRLB) of the RSSI is obtained. Then, all the anchor nodes are selected by the method, and the RSSI of the anchor nodes is obtained. Then, all the anchor node selected state combinations (selected as 1 and unselected as 0) are substituted into the CRLB formula, and the traces of the CRLB are solved by semidefinite relaxation. Finally, the selected state combination corresponding to the minimum trace is the selection result. The experimental results show that compared with the algorithm without anchor node selection, this method improves the positioning accuracy in X, Y , and Z directions by 37.6 %, 32.2 %, and 38.8 %, respectively, and it is close to the anchor node selection result of the exhaustive method. In addition, the proposed algorithm adopts an unsupervised approach without obtaining a priori data, which has high practical application value. © 2024 Northeast University. All rights reserved.
引用
收藏
页码:4217 / 4224
页数:7
相关论文
共 22 条
[1]  
Lu Y Q, Ma H J, Smart E, Et al., Real-time performance-focused localization techniques for autonomous vehicle: A review, IEEE Transactions on Intelligent Transportation Systems, 23, 7, pp. 6082-6100, (2022)
[2]  
Guo G, Liu J G, Sun X Z., Secure robust precise vehicle localization with 5G/GNSS fusion: Advances and prospects, Control and Decision, 38, 2, pp. 289-303, (2023)
[3]  
Yang B, Dai C H, Ye H Y, Et al., Research on high precision indoor positioning method based on low power bluetooth technology, The 6th International Conference on Big Data and Information Analytics, pp. 133-137, (2020)
[4]  
Carotenuto R, Merenda M, Iero D, Et al., An indoor ultrasonic system for autonomous 3-D positioning, IEEE Transactions on Instrumentation and Measurement, 68, 7, pp. 2507-2518, (2019)
[5]  
Gezici S, Tian Z, Giannakis G B, Et al., Localization via ultra-wideband radios: A look at positioning aspects for future sensor networks, IEEE Signal Processing Magazine, 22, 4, pp. 70-84, (2005)
[6]  
Guo L, Liu R, Lan F J, Et al., Object tracking based on sequence matching between UWB and LiDAR, Control and Decision, 39, 8, pp. 2613-2621, (2024)
[7]  
Zekavat R, Buehrer R M., Impact of anchor placement and anchor selection on localization accuracy, pp. 425-455, (2012)
[8]  
Qi X G, Chen Z, Li Z N., A review of non-line-of-sight identification and mitigation algorithms for indoor localization, Control and Decision, 37, 8, pp. 1921-1933, (2022)
[9]  
Courtay A, Gentil M L, Berder O, Et al., Anchor selection algorithm for mobile indoor positioning using WSN with UWB radio, IEEE Sensors Applications Symposium, pp. 1-5, (2019)
[10]  
Chen H G, Dhekne A., PnPLoc: UWB based plug & play indoor localization, IEEE the 12th International Conference on Indoor Positioning and Indoor Navigation, pp. 1-8, (2022)