Localization In Underwater Sensor Networks
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Localization in Underwater Sensor Networks
Ocean covers 70.8% of the Earth’s surface, and it plays an important role in supporting all life on Earth. Nonetheless, more than 80% of the ocean’s volume remains unmapped, unobserved and unexplored. In this regard, Underwater Sensor Networks (USNs), which offer ubiquitous computation, efficient communication and reliable control, are emerging as a promising solution to understand and explore the ocean. In order to support the application of USNs, accurate position information from sensor nodes is required to correctly analyze and interpret the data sampled. However, the openness and weak communication characteristics of USNs make underwater localization much more challenging in comparison to terrestrial sensor networks. In this book, we focus on the localization problem in USNs, taking into account the unique characteristics of the underwater environment. This problem is of considerable importance, since fundamental guidance on the design and analysis of USN localization is very limited at present. To this end, we first introduce the network architecture of USNs and briefly review previous approaches to the localization of USNs. Then, the asynchronous clock, node mobility, stratification effect, privacy preserving and attack detection are considered respectively and corresponding localization schemes are developed. Lastly, the book’s rich implications provide guidance on the design of future USN localization schemes. The results in this book reveal from a system perspective that underwater localization accuracy is closely related to the communication protocol and optimization estimator. Researchers, scientists and engineers in the field of USNs can benefit greatly from this book, which provides a wealth of information, useful methods and practical algorithms to help understand and explore the ocean.
Node Localization in Underwater Sensor Networks (UWSN)
"This dissertation focuses on node localization in underwater wireless sensor networks (UWSNs) where anchor nodes have knowledge of their own locations and communicate with sensor nodes in acoustic or magnetic induction (MI) means. The sensor nodes utilize the communication signals and the locations of anchor nodes to locate themselves and propagate their locations through the network. For UWSN using MI communications, this dissertation proposes two localization methods: rotation matrix (RM)-based method and the distance-based method. Both methods require only two anchor nodes with arbitrarily oriented tri-directional coils to locate one sensor node in the 3-D space, thus having advantages in a sparse network. Simulation studies show that the RM-based method achieves high localization accuracy, while the distance-based method exhibits less computational complexity. For UWSN using acoustic communications, this dissertation proposes a novel multi-hop node localization method in the 2-D and 3-D spaces, respectively. The proposed method estimates Euclidean distances to anchor nodes via multi-hop propagations with the help of angle of arrival (AoA) measurements. Simulation results show that the proposed method achieves better localization accuracy than existing multi-hop methods, with high localization coverage. This dissertation also investigates the hardware implementation of acoustic transmitter and receiver, and conducted field experiments with the hardware to estimate ToA using single pseudo-noise (PN) and dual PN(DPN) sequences. Both simulation and field test results show that the DPN sequences outperform the single PNs in severely dispersive channels and when the carrier frequency offset (CFO) is high"--Abstract, page iv.
Underwater Information Perception and Processing Via Underwater Sensor Networks
This book highlights the latest advances and trends in information perception and processing of underwater sensor networks (USNs). Underwater sensor networks are networks of autonomous sensor nodes distributed over a given region of water to collaboratively perform a given task. Nearly 70% of the Earth's surface is covered by water, mainly oceans, and more than 80% of the ocean remains unexplored. The emergence of USNs is a new direction in ocean exploration and data collection. USNs offer many applications in both civilian and non-civilian fields. However, due to the characteristics of underwater environments, USNs face challenges such as limited bandwidth, high propagation delay, media access control, routing, resource utilization, power limitation, etc. Researchers have studied and provided many techniques over the past decades to address these issues. This book systematically summarizes the development and covers a wide range of applications of USNs, including mobile node localization, target detection, target recognition, target tracking, sensor scheduling, and environmental monitoring. It also focuses on the introduction of new technologies, including deep reinforcement learning, into underwater information perception and processing. This book is suitable for university lecturers, graduate students, and industry professionals working in the field of USNs.