# Underwater Acoustic Target Tracking: A Review
## 5 Classification Underwater Acoustic Target Tracking Algorithms
### Classification Based on Mode-Based Method
#### 5.2.1 Passive Tracking  
The problem of tracking using passive measurements can be formulated as bearings-only tracking (BOT) which is a technology of determining the state of a target solely through measurements obtained from the signals originated from the target. Due to the inherent nonlinearity between the passive measurements and the state of the target, the design of a reliable and robust algorithm for BOT is still a challenge. In [73], since the pair of two sensors located on the towed array can give a rough estimate of the position of the target through the bearing measurement obtained individually as Figure 4 shows, the different measurements obtained with multiple sensor pairs of the towed array are given to multiple filters to obtain multiple state estimates and corresponding covariance matrices. Then these estimates are integrated by least square estimation (LSE) to obtain the final fusion result. The passively acquired bearing measurements of the targets are often corrupted by noise. If these bearing or azimuth measurements are directly used to compute the position of the target [73], even small errors in angle can result in huge position deviation. This is apparent from Figure 8. A novel tracking algorithm dealing with the BOT problem is proposed in [74], which reduce tracking errors by the pre-processing process of the obtained bearings. The preprocessing technique efficiently reduces the variance of the noise present at the bearing measurements by taking an average of the present and projected the previous measurement since the natural noise is generally unbiased. The proposed pre-processing technique makes it possible to achieve satisfactory tracking performance using passive measurements in underwater scenarios with high environmental noise. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Tracking** & **Reference** & **Precision** & **Complexity** & **Cost** & & **Strength** & **Weakness** \\ \hline Acoustic & [49] & Medium & Medium & Medium & \(\bullet\) & Have considerable tracking performance in close range. & \(\bullet\) & Low contrast \\ imaging sensor & [50] & High & Low & Low & \(\bullet\) & Obtain not only motion information but also & \(\bullet\) & Low visibility \\  & [53] & High & Medium & Medium & & features & \(\bullet\) & Low LFR \\ \hline TASA & [38] & High & Low & Low & & & & \
\begin{tabular}{c} Portugal ambiguity \\ Tracking performance depends \\ on the relative position between the target and the array \\ \end{tabular} \\  & [56] & High & Low & High & & target & & on the relative position between the target and the array \\ \hline \multirow{5}{*}{UWSNs} & [61] & Medium & Low & \(\bullet\) & Wide-range distributed & \multirow{5}{*}{
\begin{tabular}{c} Limited energy \\ Limited communication ability \\ Tracking security \\ \end{tabular} } \\  & [63] & Medium & Medium & Low & \(\bullet\) & Low cost & \(\bullet\) & Limited energy \\  & [66] & Medium & Medium & Low & \(\bullet\) & Low cost & \(\bullet\) & Limited communication ability \\  & [67] & High & Medium & Low & \(\bullet\) & Rapid deployment & \(\bullet\) & Tracking security \\  & [68] & Medium & Medium & Low & \(\bullet\) & Fault-tolerance & \\  & [71] & \(\bullet\) & Medium & Low & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of tracking instrument-assisted methods. The tracking performance can be improved by a higher order of pre-processor; however, it is at the cost of bringing the extra computation complexity and time. The optimal number of the order is left for future work. The BOT has the problem of unobservability before the single observing platform making a maneuvering. Like the work in [56] which eliminates the unobservability by adding another platform, the authors in [75] add another stationary sensor providing range information by the time-delay of the passively acquired echoes emitting from the target. With bearings measured by a sonar and the time-delay between the sonar and a sensor, the tracking performance using passive measurements has been significantly improved.