Abstract
Localization is a key-enabling technology for many applications in underwater wireless sensor networks. Traditional approaches for received signal strength (RSS)-based localization often require uniform distribution for anchor nodes and suffer from poor estimates according to unpredictable and uncontrollable noise conditions. In this paper, we establish an RSS-based localization scheme to determine the location of an unknown normal sensor from a certain measurement set of potential anchor nodes. First, we present a practical path loss model for wireless communication in underwater acoustic environments, where anchor nodes are deployed in a random circumstance. For a given area of interest, the RSS data collection is performed dynamically, where the measurement noises and the correlation among them are taken into account. For a pair of transmitter and receiver, we approximate the geometry distance between them according to a linear regression model. Thus, we can obtain a quick access for the range information, while keeping the error, the communication head and the response time low. We also present a method to correct noises in the distance estimate. Simulation results demonstrate that our localization scheme achieves a better performance for certain scenario settings. The successful localization probability can be up to 90%, where the anchor rate is fixed at 10%.
Highlights
The development of underwater wireless sensor networks (UWSNs) has openned great possibilities in several civilian and military applications such as event detection, monitoring and surveillance technologies, especially when human operation is difficult [1,2,3]
We aim to conduct several numerical simulations in order to assess the effectiveness of the proposed localization scheme
Regarding the simulation parameter settings, we consider a networks of Nnode nodes that are randomly deployed in a seabed of 1000 × 1000 × 600 m with the same amount of energy
Summary
The development of underwater wireless sensor networks (UWSNs) has openned great possibilities in several civilian and military applications such as event detection, monitoring and surveillance technologies, especially when human operation is difficult [1,2,3]. In order to track sensor nodes and to apply location-based routing algorithms, developing a localization scheme that takes environment characteristics into account is required. Only a small fraction of sensors are location-aware, while the rest of them need to be located. Underwater systems inevitably have limited capabilities in storage and computational, fundamental principles for designing localization schemes are rapidity, scalability, and reliability. The design of localization algorithms should depend on several factors including accuracy requirement, resource ability, and deployment restriction
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