# A Mobility-Assisted Localization Algorithm for Three-Dimensional Large-Scale UWSNs
## 2 Related Work
The DET is attached to the surface buoys and can DNR to broadcast its location information. Moreover, the anchor node estimates its location by receiving location messages propagated by three or more DETs. Moreover, the ordinary sensor node estimates its location by receiving messages propagated by the anchor node that has been located. However, the influence of water flow and other factors on sensor nodes is not considered in this scheme. Ordinary sensor nodes account for the highest proportion in UWSNs. However, after the anchor node is located, the ordinary sensor node is located, resulting in the accumulation of localization errors. Different from Reference [22], the authors proposed a 3D \begin{table}
\begin{tabular}{c c c} \hline \hline
**Performance Index** & **Sensor Networks** & **UWSNs** & **Terrestrial WSNs** \\ \hline Communication & Acoustic & Electromagnetic \\ Propagation Speed & Low & High \\ Propagation Delay & High & Low \\ Communication Bandwidth & Narrow & Wide \\ Data Rates & Low & High \\ Energy Consumption & High & Low \\ Noise & High & Low \\ Bit Error Rate & High & Low \\ Reliability & Low & High \\ Cost & High & Low \\ Transmission Power & High & Low \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison between underwater wireless sensor networks (UWSNs) and terrestrial wireless sensor networks (WSNs). multi-power area localization scheme (3D-MALS) in Reference [12]. In the scheme, ordinary sensor nodes regularly receive location messages propagated from the mobile DET and send the captured messages and the lowest transmission power level to sink nodes. The sink node estimates the shortest distance from the sensor node to the mobile DET. Finally, the centroid of the estimated region is used as the position of the sensor node. In this positioning scheme, the role of mobile DET is equivalent to that of mobile anchor nodes. The authors also proposed an area localization scheme for ideal channel propagation conditions in Reference [23]. Due to its also relatively ideal implementation environment, it is not introduced here. In Reference [24], the authors proposed an asymmetrical round-trip-based localization (ARTL) algorithm. The method uses an initial beacon node to send a ranging request, and then, after receiving the request, each ordinary sensor sends a relevant message to each beacon. Then the beacon only needs to store the coordinates and corresponding timestamps related to the ranging, and the actual ranging and localization estimation are completed by base stations post-mission. Since the distance measurement between the beacon node and the ordinary node is correlated with the time difference, the method does not require time synchronization. The underwater localization algorithm has good scalability and low communication overhead. However, the timeliness of sensor node location estimation is relatively insufficient. In Reference [25], a multistage AUV-aided localization scheme for UWSNs is proposed. The localization scheme uses an AUV to dive into a preset depth and starts traversing the sensor network to follow a preprogrammed path. In the first stage, the located node serves as a new reference node, and in the second stage, it assists other locating node localizations. However, the timeliness of the localization method node is relatively insufficient. Moreover, the TOA-based method is used to measure the distance between the ordinary sensor node and AUV. Therefore, the localization scheme requires time synchronization. In Reference [26], the authors proposed a range-free, passive, and AUV-based localization scheme. This localization scheme uses an AUV to periodically broadcast a message block via four directional beams. The sensor node receives the message block and uses two different successive beams to obtain the location of the AUV at two different times. Then, utilizing the two estimated positions, it can obtain the position of the node. In Reference [27], a localization scheme for large-scale UWSNs is proposed.