A Self-Localization Algorithm with Adaptive and Dynamic Observation Period for Mobile Underwater Acoustic Networks
Abstrak
In order to resolve the conflicts between the communication traffic and the localization accuracy, a self-localization algorithm with adaptive and dynamic observation period for mobile underwater acoustic networks (MUANs) was proposed to improve the localization performance. First, an adaptive and dynamic observation period selection scheme was designed, which could generate a non-uniform observation period vector according to the residual change. Then, based on the non-uniform observation period vector, a self-localization algorithm was proposed, which could precisely predict the trajectory of each mobile node in the network. The simulation results show that the proposed algorithm, which could balance the tradeoff between the localization accuracy and the communication cost, is more suitable for the underwater environment.
Topik & Kata Kunci
Penulis (1)
GAO Jingjie, WANG Wei, SHEN Xiaohong
Akses Cepat
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Cek di sumber asli →- Tahun Terbit
- 2022
- Sumber Database
- DOAJ
- DOI
- 10.16183/j.cnki.jsjtu.2021.193
- Akses
- Open Access ✓