Indoor Positioning Algorithm of Subregional Visible Light Based on Multilayer ELM

XU Yan, WANG Xinxin

Abstract

In a diffuse optical channel,the visible light indoor positioning is affected by first-order reflection and noise,and thus the positioning error in boundary region is relatively larger than that in interior region. To solve this problem,a positioning algorithm of subregional visible light indoor based on multilayer Extreme Learning Machine (ELM) was proposed in this paper,and the effectiveness of the proposed algorithm was verified by simulation experiments. Firstly,the first layer ELM based on the entire experimental region was established to calculate the entire positioning error. Secondly,the second layer ELM based on the magnitude and distribution characteristics of positioning error was established,and the entire experimental region was divided into boundary subregion and interior subregion. Thirdly,the third layer ELM based on the extracted boundary subregion was established to calculate the boundary positioning error. Lastly,the entire error with updated boundary error was used to realize the positioning. The experimental results show that the entire average positioning error of the proposed algorithm is 2.79 cm. Compared with the Received Signal Strength(RSS) and Back Propagation(BP) neural networks,the average positioning error is reduced by 13 times and 55.36%,respectively. Compared with the single-layer ELM,the boundary average positioning error is reduced by 65.66%,the entire average positioning error is reduced by 23.77%. Experimental results indicate that the boundary positioning error of the proposed algorithm is obviously decreased,which means the proposed algorithm has higher positioning accuracy and robustness,and is suitable for various positioning applications.

 

 

Keywords:  indoor positioning systems,  visible light communication,  extreme learning machine,  divided region,  received signal strength


Full Text:

PDF


References


OH J, UM J. Acoustic signal-based indoor global coordinates system for smartphones [J]. IEEE Sensors Journal, 2018, 18(8): 3248—3254.

YASSIN A, NASSER Y, AWAD M, et al. Recent advances in indoor localization: a survey on theoretical approaches and applications [J]. IEEE Communications Surveys & Tutorials, 2017, 19 (2) : 1327—1346.

LANG X M, LI P, CAO J T, et al. Study on pipeline leak detection and location based on imbalance data processing [J]. Journal of Hunan University(Natural Sciences), 2018, 45 (2) : 110—118.(In Chinese)

ZHU B C, CHENG J, WANG Y J. Three -dimensional VLC positioning based on angel difference of arrival with arbitrary tilting angel of receiver [J]. IEEE Journal on Selected Areas in Communi cations, 2018, 36 (1) : 8—22.

XU K, LIU H L, MA Z J, et al. A linear programming algorithm for indoor localization in wireless sensor networks[J] . Journal of Hunan University (Natural Sciences), 2016, 43 (8) : 115—119.(In Chinese)

WU N, WANG X D, HU Q Q, et al. Multiple LED based high accuracy indoor visible light positioning scheme [J]. Journal of Electronics & Information Technology, 2015, 37 (3) : 727—732. (In Chinese)

FANG J B, YANG Z, LONG S, et al. High-speed indoor navigation system based on visible light and mobile phone [J] . IEEE Photonics Journal, 2017, 9 (2) : 8200711.

LI Z P, JIANG M, ZHANG X N, et al. Miller-coded asynchronous visible light positioning system for smart phones [C] // IEEE 85th Vehicular Technology Conference. Sydney: IEEE, 2017: 1—6.

IFTHEKHAR M S, SAHA N, JANG Y M. Neural network based in door positioning technique in optical camera communication system [C] //2014 International Conference on Indoor Positioning and Indoor Navigation. Busan, Korea: IEEE, 2015: 431—435.

LI P, WANG Y J. Multi -target tracking algorithm based on ORB feature points matching [J] . Journal of Hunan University(Natural Science), 2017, 44 (10) :139-149.(In Chinese)

ZHANG W Z, CHOWDHURY M I S, KAVEHRAD M. Asynchronous indoor positioning system based on visible light communications[J]. Optical Engineering, 2014, 53 (4) : 045105.

HUANG H Q, YANG A Y, FENG L H, et al. Artificial neural-network-based visible light positioning algorithm with a diffuse optical channel [J]. Chinese Optical Letters, 2017, 15 (5) : 050601.


Refbacks

  • There are currently no refbacks.