A Novel Localization Approach for Irregular Wireless Sensor Networks Based on Anchor Segmentation

Jing Wang, Li Cheng, Yuanfei Tu, Shenkai Gu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Source localization has been a crucial fundamental service in wireless sensor networks (WSNs). Existing algorithms assume a regular region or controlled deployment. In practice, however, irregular network topologies often occurs, which greatly downgrade the localization performance. In this paper, we propose a new distributed localization approach based on Anchor Segmentation and Projection for Irregular networks (ASPI). The new framework is composed of three phases: anchor segmentation boarder construction, convex hull identification and projection-based localization. An anchor based network approximate convex segmentation method is proposed to reduce the consumption of network resources in the first two phases and an improved giftwrapping based convex hull identification method is provided to reduce the complexity. In the localization phase, we formulate the localization as a convex feasibility problem to avoid the multimodality in Maximum likelihood techniques and an alternative procedure is provided for inconsistent situation in the projection-based scheme. Experiments are conducted and the results demonstrate that our algorithm outperforms other existing solutions in irregular-shaped networks in higher accuracy with low complexity.

Original languageEnglish
Pages (from-to)7267-7276
Number of pages10
JournalIEEE Sensors Journal
Volume22
Issue number7
DOIs
StatePublished - 1 Apr 2022

Keywords

  • Convex feasibility problem
  • Convex segmentation
  • Wireless sensor networks

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