# A Mobility-Assisted Localization Algorithm for Three-Dimensional Large-Scale UWSNs
## 2 Related Work  
Many excellent localization algorithms based on terrestrial WSNs have been proposed [14; 15]; however, these algorithms cannot be directly applied to underwater environments. To cope with the complex and varied conditions of the underwater environment, some related scholars have also proposed some underwater localization schemes based on UWSNs and reviewed relevant literature [16; 17; 18]. However, it is not enough. In this section, we compare UWSNs and terrestrial WSNs. Moreover, some excellent underwater localization algorithm papers related to this paper are discussed and summarized. UWSNs are more complex and challenging than terrestrial WSNs. The area where the terrestrial WSN is deployed has a height much smaller than its length and width. Normally, its localization problem can be converted into a 2D plane positioning. However, the depth of the underwater monitoring environment cannot be ignored. Hence, underwater sensor node localization is usually 2D localization of a depth plane or 3D localization of a water space. Sensor nodes use electromagnetic waves to communicate on land. Their communication bandwidth, propagation delay, and bit error rate are better than those of UWSNs. Moreover, the sensor node locations of terrestrial WSNs are relatively fixed. The topology of the network does not evolve dynamically, so it is not necessary to consider the movement under the action of external forces. However, underwater sensor nodes are susceptible to the influence of water flow and other factors to generate relative motion. A relevant summary comparison of UWSNs and WSNs is shown in Table 1.  
In Reference [19], the idea of using dive-and-rise (DNR) anchor nodes to locate sensor nodes is proposed. Anchor nodes dive by attaching additional weights. Then, at a certain depth, the weight is released, and the anchor nodes rise. These anchor nodes use GPS to obtain coordinates before sinking, and they transmit location information during diving. It is assumed that all sensor nodes are equipped with UPS to obtain their depth information. The authors consider two states of the sensor node, namely, static and free-drifting nodes. Then, The TOA-based method is used to achieve distance measurement between sensor nodes and mobile anchor nodes. Finally, the bounding box method and triangulation localization scheme are used to estimate the sensor node position. However, time synchronization is difficult to achieve underwater. In Reference [20], the authors proposed a time-synchronization-free localization scheme by utilizing mobile beacon nodes. The scheme assumes that the mobile beacon nodes dive and rise vertically underwater, at a constant speed. All nodes are relatively static and are not affected by factors such as water flow. Ordinary nodes can estimate the distance to the mobile beacon node by receiving the position information transmitted by the beacon node at two different times. Furthermore, the localization method also assumes that all sensor node equipment is located with UPS. Finally, the location of the sensor node is estimated by using the least square (LS) method. Although this method has certain reference values for the localization scheme without time synchronization, the scheme is implemented in a relatively ideal underwater environment. Based on Reference [20], a two-phase time-synchronization-free localization algorithm is proposed [21]. In the first phase, the mobile anchor nodes are used to locate ordinary sensor nodes in the monitoring area. In the second phase, ordinary sensor nodes that have been located in the first phase are taken as new reference nodes, and then the nodes that have not been located are repositioned. However, the implementation environment of this method is also relatively ideal. In Reference [22], a hierarchical localization scheme for large-scale UWSNs is proposed. In the localization scheme, sensor nodes are divided into four types, namely, surface buoys, DETs, anchor nodes, and ordinary nodes. Surface buoys can obtain location information by using GPS.