UWB Hybrid Filtering-Based Mobile IoT Device Tracking

Boliang Zhang, Lu Shen, Jiahua Yao, Su Kit Tang, Silvia Mirri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The positioning accuracy of UWB-based mobile Internet of Things (IoT) devices is frequently impacted by the complicated indoor environment, which is a common application for automated following mobile IoT devices. To address the issue of abnormal value errors such as high noise and UWB jitter value when tracking and locating mobile IoT devices in complicated indoor environments, this paper proposes to use a hybrid filtering weighted following algorithm based on UWB, which combines the benefits and drawbacks of Gaussian, median, and average filtering techniques, introduces the residual value of ranging, and combines geometric positioning to determine the ideal following value. The experimental results show that the proposed algorithm can effectively filter out the UWB error under multi-factor interference and finally estimate the UWB value closest to the actual value, thereby improving the stability and sensitivity of the following process and obtaining a better follow effect.

Original languageEnglish
Title of host publicationGoodIT 2023 - Proceedings of the 2023 ACM Conference on Information Technology for Social Good
PublisherAssociation for Computing Machinery
Number of pages6
ISBN (Electronic)9798400701160
Publication statusPublished - 6 Sept 2023
Event3rd ACM Conference on Information Technology for Social Good, GoodIT 2023 - Lisbon, Portugal
Duration: 6 Sept 20238 Sept 2023

Publication series

NameACM International Conference Proceeding Series


Conference3rd ACM Conference on Information Technology for Social Good, GoodIT 2023


  • IoT
  • UWB jitter value
  • following algorithm
  • hybrid filtering
  • indoor positioning


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