# Underwater Acoustic Target Tracking: A Review
## 5 Classification Underwater Acoustic Target Tracking Algorithms
### Quantized Methods  
Although the raw measurements can provide more accurate information about the target, the limited communication bandwidth and energy make quantized measurements preferable in underwater environment. There is a large amount of papers focus on quantizer design in WSNs [34; 69]. On the condition of fixed allowable energy for transmitting a message, the authors in [99] investigate the optimal number of quantization bits and energy allocation strategy to minimize the error of reconstruction. A new distributed quantization method is proposed in [100]. The sensor can automatically adjust its quantization threshold based on the earlier transmission from other sensor nodes. However, the adaptive adjustment of step size, which determines the value of quantization threshold, need further research. Some researchers investigate optimal quantization methods from the aspect of information gain [101; 102]. Except for the quantized methods with fixed threshold, the proposed algorithms in WSNs have the common weak in relying on the target current state and requiring heavy computation burden. In underwater target tracking, there are only a few studies on quantized methods. The authors in [67] investigate the influence of node topology on the under tracking performance with quantized measurements. However, the quantized threshold is fixed. Considering most quantization methods in WSNs need complex computation, a simplified objective function for determining the optimal quantization threshold offline is proposed in [103]. By minimizing the expectation of additional error covariance incurred by quantized measurements, the function optimal quantization factor is derived. The factor can be predetermined because it is independent on the sensor location and target state, which significantly eases the computation burden on sensors. The existing WSN quantized methods can be extended to the underwater environment, although constraints such as energy and communication bandwidth are more serious underwater than in WSNs. Optimal quantization methods, especially for underwater acoustic target tracking, need further research. Traditionally, when it comes to the tracking results optimization, filtering techniques are the first choice while other optimization methods have been ignored. However, there is a great attempt to consider technologies from other subjects to improve the tracking performance. Through the simple description of the arithmetic average and the Sage-Husa model, the researchers can find ideas for tracking optimization not constrained to the filtering techniques. Moreover, the relevant sources of application scenarios must also be considered. That's why we take the tracking optimization method as a classification criterion. Then we compare these papers in Table 5 in the aspect of precision, computation complexity, tracking response time, and corresponding disadvantages. As Table 5 shows, the quantization issue in underwater acoustic tracking have not well studied. However, the bandwidth constraint is much serious in marine environment. More attention should be paid to investigating the quantized methods suitable for underwater tracking.