Indoor Positioning Technique applying new RSSI Correction method optimized by Genetic Algorithm
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques usingWi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, apopular method widely used for indoor positioning, however, it improves some disadvantages of the WeightedCentroid method and also for other kinds of indoor positioning methods, by using the received signal strengthcorrection method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is causedby the complex propagation environment. To validate the performance of the proposed algorithm, we conductedexperiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several accesspoints around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracypositioning system, which can be used in any building environment with an available Wi-Fi access point setup asa beacon node.
Abstract
In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques usingWi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, apopular method widely used for indoor positioning, however, it improves some disadvantages of the WeightedCentroid method and also for other kinds of indoor positioning methods, by using the received signal strengthcorrection method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is causedby the complex propagation environment. To validate the performance of the proposed algorithm, we conductedexperiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several accesspoints around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracypositioning system, which can be used in any building environment with an available Wi-Fi access point setup asa beacon node.
참고문헌 (19)
- L. Brás, "Improved sectorised antenna for indoor localization systems", Proc. of 2011 41st European Microwave Conference, pp.1003~1006 (2011)
- D. Tang, "Design of the Frequency Selective Directional Indoor Positioning Beacon Antenna", Proc. of 2020 2nd International Conference on Information Technology and Computer Application (ITCA), pp.437~440 (2020)
- G. Huo, "Design of a High Accuracy and RealTime Indoor Positioning System Based on Coding Point Identification and its FPGA Implementation", Proc. of 2020 4th IEEE Electron Devices Technology & Manufacturing Conference (EDTM), pp.1~4 (2020)
- G. Wu, "A Deep Neural NetworkBased Indoor Positioning Method using Channel State Information", Proc. of 2018 International Conference on Computing, Networking and Communications (ICNC), pp.290~294 (2018)
- N. Lee, "Magnetic indoor positioning system using deep neural network", Proc. of 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp.1~8 (2017)
- M. Hazas, "Broadband ultrasonic location systems for improved indoor positioning", IEEE Transactions on Mobile Computing, 5(5), pp.536~547 (2006), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- P. Bahl, "RADAR: An in-building rf-based user location and tracking system", Proc. of INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, pp.775~784 (2000)
- I. Guvenc, "Enhancements to RSS based indoor tracking systems using kalman filters", Proc. of GSPx & international signal processing conference, pp.91~102 (2003)
- M. Youssef, "The horus WLAN location determination system", Proceedings of the 3rd international conference on Mobile systems, applications, and services, pp.205~218 (2005)
- M. Kotaru, "Spotfi: Decimeter level localization using WiFi", Proc. of ACM SIGCOMM Computer Communication Review, pp.269~282 (2015)
- J. Xiong, "ArrayTrack: a fine-grained indoor location system", Proc. of Presented as part of the 10th USENIX Symposium on Networked Systems Design and Implementation (NSDI 13), pp.71~84 (2013)
- P. Dabove, "Indoor positioning using Ultra-wide band (UWB) technologies: Positioning accuracies and sensors’ performances", Proc. of 2018 IEEE, 2018, 175~184
- A. A. Kalbandhe, "Indoor Positioning System using Bluetooth Low Energy", Proc. of 2016 International Conference on Computing, Analytics and Security Trends (CAST), pp.451~455 (2016)
- L. Ru, "A weighted centroid localization algorithm for wireless sensor networks based on weight correction", Proc. of 2017 9th International Conference on Advanced Infocomm Technology (ICAIT), pp.165~169 (2017)
- R. Joseph, "Indoor Positioning Using WiFi Fingerprint", Proc. of 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET), pp.1~3 (2018)
- H. Shi, "A new weighted centroid localization algorithm based on RSSI", Proc. of 2012 IEEE International Conference on Information and Automation, pp.137~141 (2012)
- G. Li, "An Indoor Positioning Algorithm Based on RSSI Real-time Correction", Proc. of 2018 14th IEEE International Conference on Signal Processing (ICSP), pp.129~133 (2018)
- Song-Hao, Jia, "Difference Correction RSSI Location Algorithm of Double Reference Nodes", Sensors and Transducers, 167, pp.75~79 (2014)[DOI]
- L. Kaikai, "A practical UWB TOA estimator in the presence of interference and NLOS", Proc. of IEEE 10th International Conference on Signal Proceedings, pp.2448~2451 (2010)
