Path Planning for Mobile-Anchor Based Wireless Sensor Networks Localization: Obstacle-Presence Schemes

Creative Commons License

Yıldız D., Karagöl S.

SENSORS, cilt.21, sa.11, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 21 Sayı: 11
  • Basım Tarihi: 2021
  • Doi Numarası: 10.3390/s21113697
  • Dergi Adı: SENSORS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Communication Abstracts, Compendex, EMBASE, INSPEC, MEDLINE, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: localization, mobile anchor node assisted localization, obstacle-handling, path planning, static path planning
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

In many Wireless Sensor Network (WSN) applications, the location of the nodes in the network is required. A logical method to find Unknown Nodes (UNNs) in the network is to use one or several mobile anchors (MAs) equipped with GPS units moving between UNNs and periodically broadcast their current location. The main challenge at this stage is to design an optimum path to estimate the locations of UNNs as accurately as possible, reach all nodes in the network, and complete the localization process as quickly as possible. This article proposes a new path planning approach for MA-based localization called Nested Hexagon Curves (NHexCurves). The proposed model's performance is compared with the performance of five existing static path planning models using Weighted Centroid Localization (WCL) and Accuracy Priority Trilateration (APT) localization techniques in the obstacle-presence scenario. With the obstacle-handling trajectories used for the models, the negative impact of the obstacle on the localization is reduced. The proposed model provides full coverage and high localization accuracy in the obstacle-presence scenario. The simulation results show the advantages of the proposed path planning model with the H-curve model over existing schemes.