@inproceedings{9461268cc2564a67bfd62a9804810e21,
title = "Localization of Unknown Number of Underwater Acoustic Signal Sources Using Underwater Sensor Network",
abstract = "The estimation of the number and locations of multiple energy sources in underwater (UW) environment is considered in the work using a clustered sensor network (SNet). Sensors are deployed on the seabed to measure the equivalent acoustic energy transmitted by all potential sources, then the received amount of energy is quantized, modulated and sent to cluster heads (CHDs) which are buoys fixed on the water-surface. The CHDs in role forward the received decisions to a data central device (DCD) using decode and forward relaying (DFR) mechanism. At the DCD side, the penalized maximum likelihood estimator (PMLE) is invoked to localize an unknown number of acoustic sources. The performance of the system is assessed by using Monte-Carlo simulations where the obtained results demonstrate the superiority of the introduced PMLE over centroid based localization method benchmark.",
keywords = "acoustic signal, Bayesian information criterion (BIC), penalized maximum likelihood estimator (PMLE), Underwater sensor network (UW-SNet)",
author = "Al-Jarrah, \{Mohammad A.\} and Emad Alsusa and Tasneem Assaf and Arafat Al-Dweik",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024 ; Conference date: 17-11-2024 Through 20-11-2024",
year = "2024",
doi = "10.1109/MECOM61498.2024.10881495",
language = "British English",
series = "2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "217--222",
booktitle = "2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024",
address = "United States",
}