A Least Square Dynamic Localization Algorithm Based on Statistical Filtering Optimal Strategy

  • Xiaozhen YanEmail author
  • Zhihao Han
  • Yipeng Yang
  • Qinghua Luo
  • Cong Hu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 516)


In wireless sensor network localization, many anchor nodes and target node exchange information at specified time intervals to obtain the distance information between each anchor node and the target node. With this information, the coordinates of the target node can be achieved through the calculation of the positioning algorithm. However, as there are numerous negative factors like non-line-of-sight measurement, complex multipath fading, which leads to high-level localization error. To improve localization accuracy, an improved least square localization algorithm is proposed, which combines the least square localization method with the statistical filtering optimization strategy. The simulation results show that this algorithm can effectively reduce localization error and achieve more accurate localization.


Wireless sensor networks Localization Least square method Extended Kalman filter Particle filter 



The research presented in this paper is supported by the National Natural Science Foundation of China (61671174, 61601142), the Natural Science Foundation of Shandong Province of China (ZR2015FM027), WeiHai Research program of Science and Technology (16), the Laboratory of Satellite Navigation System and Equipment Technology (EX166840037, EX166840044), the Guangxi Key Laboratory of Automatic Detecting Technology and Instruments (YQ18206,YQ15203), the Natural Scientific Research Innovation Foundation of the Harbin Institute of Technology (HIT.NSRIF.2015122), the State Key Laboratory of Geo-information Engineering (SKLGIE2014-M-2-4), and Discipline Construction Guiding Foundation in Harbin Institute of Technology (Weihai) (WH20150211).


  1. 1.
    Peng Y, Wang D. A review: wireless sensor network localization. J Electron Meas Instrum. 2011;25(5):389–99.CrossRefGoogle Scholar
  2. 2.
    Kim E, Kim K. Distance estimation with weighted least squares for mobile beacon-based localization in wireless sensor networks. IEEE Signal Process Lett. 2010;17(6):559–62.CrossRefGoogle Scholar
  3. 3.
    Cheng J, Yang L, Li Y, et al. Seamless outdoor/indoor navigation with WIFI/GPS aided low cost Inertial Navigation System. Phys Commun. 2014;13(PA):31–43.CrossRefGoogle Scholar
  4. 4.
    Ades M, Van Leeuwen PJ. An exploration of the equivalent weights particle filter. Q J R Meteorol Soc. 2013;139(672):820–40.CrossRefGoogle Scholar
  5. 5.
    Huang CH, Lee LH, Ho CC, et al. Real-time RFID indoor positioning system based on Kalman-filter drift removal and Heron-Bilateration location estimation. IEEE Trans Instrum Meas. 2015;64(3):728–39.CrossRefGoogle Scholar
  6. 6.
    Jiaojiao W. Research on wireless localization technology of indoor moving target. TianJing University master thesis; 2013. p. 19–31.Google Scholar
  7. 7.
    Juan M, Li H, Yanan L, et al. Modified least squares-BFGS positioning algorithm based on dynamic T-test. Comput Appl Softw. 2016;22(6):126–9.Google Scholar
  8. 8.
    Mirzaei HR, Akbari A, Gockenbach E, et al. A novel method for ultra-high-frequency partial discharge localization in power transformers using the particle swarm optimization algorithm. IEEE Electr Insul Mag. 2013;29(2):26–39.CrossRefGoogle Scholar
  9. 9.
    Yao Y. Polaronic quantum diffusion in dynamic localization regime. New J Phys. 2017;19(4):043015.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Xiaozhen Yan
    • 1
    • 2
    Email author
  • Zhihao Han
    • 1
  • Yipeng Yang
    • 1
  • Qinghua Luo
    • 1
    • 2
  • Cong Hu
    • 2
  1. 1.School of Information Science and EngineeringHarbin Institute of Technology at WeihaiWeihaiChina
  2. 2.Guangxi Key Laboratory of Automatic Detecting Technology and InstrumentsGuilin University of Electronic TechnologyGuilinChina

Personalised recommendations