Localization Scheme with MAP Pre-filter in Wireless Sensor Network Combating Intensive Measurement Noise

  • Zhuangkun Wei
  • Yongjun Zhang
  • Bin Li
  • Chenglin Zhao
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 463)


Increasing advances in building reliable and efficient wireless sensor network (WSN) provide a promising prospect in the applications of monitoring and localization. However, due to the intensive measurement noise, observations from sensors can be severely deteriorated, rendering most existing localization schemes unattractive. In this paper, we propose a new localization scheme, which can obtain more reliable observations from the deteriorated ones, and improve the localization performance. That is, we design a maximum a posterior (MAP) pre-filter, which can filter out the measurement noise, and derive the more reliable filtered observations. Then such filtered observations will be adopted in the sequential two-phase Bayesian process, which combines the priori estimative results and the current filtered observations to derive the current estimative localization. Numerical simulations validate the new localization scheme, which can indeed obtain a better performance than traditional schemes.


Wireless sensor network (WSN) Localization Two-phase Bayesian process MAP pre-filter 



This work is supported by National Science and Technology Major Project 2014ZX03001027 and the Natural Science Foundation of China 61379016.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Zhuangkun Wei
    • 1
  • Yongjun Zhang
    • 1
  • Bin Li
    • 1
  • Chenglin Zhao
    • 1
  1. 1.School of Information and Communication EngineeringBeijing University of Posts and TelecommunicationsBeijingChina

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