HU Bing, PENG Huijun, SUN Zhixin, “LANDMARC Localization Algorithm Based on Weight Optimization,” Chinese Journal of Electronics, vol. 27, no. 6, pp. 1291-1296, 2018, doi: 10.1049/cje.2017.08.011
Citation: HU Bing, PENG Huijun, SUN Zhixin, “LANDMARC Localization Algorithm Based on Weight Optimization,” Chinese Journal of Electronics, vol. 27, no. 6, pp. 1291-1296, 2018, doi: 10.1049/cje.2017.08.011

LANDMARC Localization Algorithm Based on Weight Optimization

doi: 10.1049/cje.2017.08.011
Funds:  This work is supported by the National Natural Science Foundation of China (No.61373135, No.61672299), the Research Project of Jiangsu Province (No.BY2013011), and the Natural Science Foundation of Jiangsu Province of China (No.BK20140883).
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  • Corresponding author: SUN Zhixin (corresponding author) was born in Anhui Province, China. He is now a professor and Ph.D. supervisor of the College of Internet of Things in Nanjing University of Posts and Telecommunications. His research interests include computer networks and security, multimedia communication, and mobile Internet. (
  • Received Date: 2017-01-12
  • Rev Recd Date: 2017-03-03
  • Publish Date: 2018-11-10
  • In order to solve the problem that the difference of Received signal strength (RSS) between tags will become large when tags are close to the reader, which exists in LANDMARC system, a LANDMARC localization algorithm based on weight optimization is proposed in the paper. We optimize the weight by redefining the formulas of in-weight and ex-weight. In-weight formula is discussed under the free space propagation model. The definition of ex-weight is obtained by analyzing the relationship between RSS and distance under the log-distance path loss model. We evaluate the performance of the proposed algorithm and compare it with the algorithm based on normalized weight. The simulation results show the superior performance of the proposed algorithm in terms of location accuracy.
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  • T.J.S. Chowdhury, C. Elkin, V. Devabhaktuni, et al., “Advances on localization techniques for wireless sensor networks: A survey”, Computer Networks, Vol.110, pp.284-305, 2016.
    N. Pirzada, M.Y. Nayan, F.S.M.F. Hassan, et al., “Device-free localization technique for indoor detection and tracking of human body: A survey”, Procedia -Social and Behavioral Sciences, Vol.129, pp.422-429, 2014.
    Y.H. Huang, S.L. Lv, Y.W. He, et al., “An isosceles triangular placement of reference tags for RFID indoor location system”, Chinese Journal of Electronics, Vol.20, No.3, pp.504-510, 2011.
    H.Q. Zhang, X.W. Shi, G.H. Deng, et al., “Research on indoor location technology based on back propagation neural network and Taylor series”, Acta Electronica Sinica, Vol.40, No.9, pp.1876-1879, 2012. (in Chinese)
    K.J. Mao, J.B. Wu, H.B. Jin, et al., “Indoor localization algorithm for NLOS environment”, Acta Electronica Sinica, Vol.44, No.5, pp.1174-1179, 2016. (in Chinese)
    Z. Deng, Y. Yu, X. Yuan, et al., “Situation and development tendency of indoor positioning”, China Communications, Vol.10, No.3, pp.42-55, 2013.
    N. Pritt, “Indoor location with Wi-Fi fingerprinting”, Proc. of IEEE Applied Imagery Pattern Recognition Workshop: Sensing for Control and Augmentation, Washington, DC, USA, pp.1-8, 2013.
    C. Jihong, “Patient positioning system in hospital based on zigbee”, Proc. of International Conference on Intelligent Computation and Bio-Medical Instrumentation, Wuhan, China, pp.159-162, 2011.
    J. Mi and Y. Takahashi, “Low cost design of HF-band RFID system for mobile robot self-localization based on multiple readers and tags”, Proc. of IEEE International Conference on Robotics and Biomimetics, Zhuhai, China, pp.194-199, 2015.
    M.M. Saad, C.J. Bleakley, T. Ballal, et al., “High-accuracy reference-free ultrasonic location estimation”, IEEE Transactions on Instrumentation and Measurement, Vol.61, No.6, pp.1561-1570, 2012.
    K.H. Chang, “Bluetooth: A viable solution for IoT? [Industry Perspectives]”, IEEE Wireless Communications, Vol.21, No.6, pp.6-7, 2014.
    L.M. Ni, Y. Liu, Y.C. Lau, et al., “LANDMARC: Indoor location sensing using active RFID”, Wireless Networks, Vol.10, No.6, pp.701-710, 2004.
    K. Han and S.H. Cho, “Advanced LANDMARC with adaptive k-nearest algorithm for RFID location system”, Proc. of International Conference on Network Infrastructure and Digital Content, Beijing, China. pp.24-26, 2010.
    Y. Zhao, Y. Liu and L.M. Ni, “VIRE: Active RFID-based localization using virtual reference elimination”, Proc. of International Conference on Parallel Processing, Xi'an, China, pp.56-63, 2007.
    G. Jin, X. Lu and M.S. Park, “An indoor localization mechanism using active RFID tag”, Proc. of IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing, Taichung, China, pp.1-4, 2006.
    H.Y. Yu, J.J. Chen and T.R. Hsiang, “Design and implementation of a real-time object location system based on passive RFID tags”, IEEE Sensors Journal, Vol.15, No.9, pp.5015-5023, 2015.
    L.N. Li, J. Ma, Y. Long, et al., “Double stage indoor localization algorithm based on LANDMARC and copressive sensing”, Journal of Electronics and Information Technology, Vol.38, No.7, pp.1631-1637, 2016.
    T. Sansanayuth, P. Suksompong, C. Chareonlarpnopparut, et al., “RFID 2D-localization improvement using modified LANDMARC with linear MMSE estimation”, Proc. of 13th International Symposium on Communications and Information Technologies, Samui Island, Thailand, pp.133-137, 2013.
    C.H. Yeh and S.F. Su, “Enhance LANDMARC from the fundamentals”, Proc. of International Conference on Advanced Robotics and Intelligent Systems, Tainan, China, pp.23-27, 2013.
    H. Aghasi, M. Hashemi and B.H. Khalaj, “Source localization through adaptive signal attenuation model and time delay estimation”, Proc. of 18th International Conference on Telecommunications, Ayia Napa, Cyprus, pp.151-156, 2011.
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