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Efficient and Accurate Target Localization in Underwater Environment

Inam UllahCollege of Internet of Things (IoT) Engineering, Hohai University (HHU), Changzhou Campus, Changzhou, ChinaYiming LiuCollege of Internet of Things (IoT) Engineering, Hohai University (HHU), Changzhou Campus, Changzhou, ChinaXin SuCollege of Internet of Things (IoT) Engineering, Hohai University (HHU), Changzhou Campus, Changzhou, ChinaPankoo KimDepartment of Computer Engineering, Chosun University, Gwangju, South Korea
2019en
ABI

Annotatsiya

Localization is the basic feature of wireless sensor networks (WSN) and estimating the time difference of arrival (TDoA), and angle of arrival (AoA) is the most used schemes for localization. Underwater wireless sensor network (UWSN) is extensively used for data collection in an underwater environment for both military and civilian applications. Nevertheless, efficient and accurate localization algorithms are essential for the UWSN because of the dynamical property of the underwater surrounding. Also, data management, collection, and processing for WSNs have become a more active topic nowadays in computer science, such as database system and data mining. The objective of deploying the WSNs applications is to collect the real-time data, which has very challenging due to the capacity of communication and high data generated by WSNs. For this purpose, the time and location are the basic aspects when a sensor collects data, especially for the case of location-aware data. Many researchers have studied the underwater sensor nodes localization and they have considered the sensor location where the data is collected and most of them focused on the fixed sensor nodes. In this research work, energy efficient and accurate localization schemes are presented named as distance-based and angle-based schemes for the underwater environment with relatively less energy consumption and mean estimation errors (MEEs). The proposed schemes mainly focus on the localization of underwater nodes and especially on the MEEs in localization. The extensive simulation is performed to compare the proposed schemes with other counterpart schemes. The results show that the proposed schemes outperform other counterpart schemes in terms of MEEs of localization and energy consumption.

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