# Research on Localization Algorithms Based on Acoustic Communication for Underwater Sensor Networks
## 1 Introduction  
The water covers over 70% of the earth while just a small part of it has been discovered. As a significant body of the land, the water contributes to the transportation, nourishment and natural resources, etc. Therefore, how to make use of water resources becomes a hot topic, and plenty of research results have been reported. Underwater Sensor Networks (UWSNs), which can be used for underwater explorations, are a valuable research direction for realizing the underwater applications. UWSNs consist of a number of autonomous and individual sensor nodes [1]. Those sensor nodes are spatially distributed in underwater and carry out some sensing work aiming at obtaining water-related properties [2]. Various applications handle sensed data based on UWSNs with different demands. The state of the sensor node can be stationary, mobile or hybrid, which can transmit the information by the wireless connectivity. Meanwhile, Wireless Sensor Networks (WSNs) and many efficient technologies have been presented such as GPS, Radio Frequency (RF), and Visible Light Communication (VLC) for the terrestrial positioning. However, the frequencies of RF signals that are suitable for use in UWSNs are only 30-300 Hz. Meanwhile, there is a requirement that the antenna is large or the transmission power is high. The optical signals also suffer from the attenuation and scattering in the underwater. Hence, both of the technologies are not suitable for UWSNs. Fortunately, acoustic waves frequency is low lying between 10 Hz and 1 MHz [1], which can offer small bandwidth but has long wavelengths. It means that the acoustics can be used for relaying information over kilometers [3]. Acoustic communication establishes the links by using the propagation of the soundwaves, which still suffer some challenges. In our paper, we will introduce localization algorithms based on acoustic communication for underwater sensor networks. Thanks to the limitations of the computational power, the memory, the cost, the communication range and the lifetime of an individual sensor, the deployment of UWSNs is still a challenging job [1]. How many sensor nodes are arranged is a problem to which we should pay attention. A greater number of sensor nodes means a larger coverage range and higher precision but may increase the cost. As we know, the power of the sensor node is limited, which means that an effective strategy should be proposed to the system performance without shortening the operating time. In [1], the authors describe the difference between UWSNs and terrestrial sensor networks in three aspects, namely, dynamics, being error-prone and 3D. In UWSNs, the sensor node can move with the ocean currents, which lead to the property of dynamics. In addition, numerous factors such as water temperature, signal attenuation, dynamics, and noise may affect the performance of the sensor network, which results in the highly sensitive property. In addition, the random deployment of nodes forms the 3D architecture underwater. In the terrestrial WSN, localization is a critical application and plenty of research results have been published. However, as we presented before, those types of signals (RF, optical signal) suffer the attenuation in the underwater. Underwater, the nodes can be divided into two types: the anchor node for which the position is known and the unknown node for which the position needs to be obtained by the localization algorithm [4]. Many types of methods can obtain the positioning information of the anchors. There we list two of them. First, the anchor node can be fixed at the known position, which means that the coordinates of the anchors are pre-configured. Second, the anchors can use specialized hardware to obtain their location such as GPS. In general, positioning algorithms use the distance or the angle information to localize the unknown node. The localization techniques can be classified into angulation and lateration [4]. The angulation uses the angle information while the literature uses the distance information.