# Underwater Acoustic Target Tracking: A Review
## 3 Knowledge of Acoustic Target Tracking Instruments
### Uwsns  
To address the aforementioned problems, UWSNs, variations of WSNs, are envisioned to enable applications for underwater target tracking. UWSNs have superiority over TASA in low-cost, self-organization, fault tolerance and rapid deployment [28]. UWSNs consist of numerous resource-constrained sensors called sensor nodes. These sensors are equipped with a limited capacity of data processing and communication via acoustic modems [29]. The target tracking problems based  
Figure 1: Bistatic source-target-receiver geometry for tracking the interested target.  
on UWSNs can be described as follows. Many homogeneous or heterogeneous sensors are deployed randomly or strategically across the interested area [30]. When the presence of single or multi-target is detected by sampling the sensed signals, these readings from multi-sensors can be used to compute the position of the target and then transmitted to the sink node which has stronger processing ability and generally serves as a gateway connecting the network and application users. After collecting data from sensors in the network, the sink node performs data fusion to provide more accurate position information and estimate the trajectory of the target being tracked [31]. The basic model of UWSNs is shown in Figure 2. Many applications contain the prediction step because the prediction result can be used to reduce energy consumption by activating the set of sensor nodes located in the region where the target is moving [32]. As sensor nodes have the energy restriction, the energy consumption is a key factor for any target tracking algorithms based on UWSNs. To be clear, we identify some components related to underwater target tracking based on UWSNs:  
* _Node localization_. Due to the severe attenuation of electromagnetic waves, the global positioning system (GPS) is unable to provide localization service for the underwater sensor nodes. Effective node localization algorithms are in need and the accuracy of the node localization has a significant impact on tracking performance.
* _Node occupation_. It defines how to communicate between nodes to reduce the amount of message transmitting.
* _Position computation_. Measurements obtained from underwater sensor nodes are severely interrupted by noise which cannot be ignored, therefore, how to use these noisy measurements to obtain the position of the target as close to the true one as possible becomes a challenging issue.
* _Future-position estimation_. Although this process is not necessary for every tracking algorithm, there are many algorithms that take into consideration this information that can be used to save energy consumption of sensor nodes by efficient node scheduling strategies.
* _Energy management_. Because the power of sensor nodes is limited, any tracking algorithms should achieve a good trade-off between tracking accuracy and energy consumption which directly determines the lifetime of the network.  
In terrestrial WSNs, as a critical application, target tracking has been well studied and plenty of research results have been published [33; 34; 35; 36]. However, considering the mobility of sensor nodes resulting from ocean current, limited communication bandwidth and the high propagation delay which are three orders of magnitude higher than that in WSNs, these technologies for WSNs cannot be directly applied to underwater target tracking. We must investigate new algorithms suitable for ocean tracking applications. Therefore, in this paper, we also have a brief overview of target tracking algorithms based on UWSNs.  
Figure 2: A model of UWSNs.  
With the development of autonomous underwater vehicles (AUVs), incorporating TASA with UWSNs, a novel variation tracking system of USWNs has been proposed, which is composed of mobile sensor nodes such as the AUVs towing acoustic arrays [37; 38].