# Positioning Systems for Unmanned Underwater Vehicles: A Comprehensive Review
## 6 Discussion
Reference [15] stands out by providing an accuracy range between 0.1% and 5%, with errors of less than 0.1 m, specifically in complex terrain environments. This quantitative information allows for a solid evaluation of how underwater terrain can significantly impact system accuracy. Similarly, [53] offers an accuracy range of 0.8% to 3.3%, with corresponding errors of 1.2 m and 8.3 m across two test runs. The degradation of accuracy here is attributed to improper compass calibration and interference from nearby magnetic fields, illustrating how environmental factors can skew positioning results. The author of [107] reports impressive accuracy, with errors around 3 mm at short distances, increasing to 0.1 m at a 10 m range. This highlights a key trend in underwater positioning systems: accuracy tends to decrease as range increases. Such precise data are crucial in evaluating system limitations and identifying areas for improvement. The paper referenced as [109] similarly provides accuracy values between 0.003 m and 0.0089 m, further emphasizing the level of precision that modern systems can achieve under controlled conditions. Additionally, [110] offers a small but noteworthy accuracy measure of 0.01\({}^{\circ}\), which is reported to degrade due to extreme depth conditions. Such precision is valuable for high-depth navigation applications where even small errors can have significant impacts. Reference [86] also provides a quantitative assessment, reporting an accuracy degradation of \(+/-15\)% under varying sea states, highlighting the role of environmental conditions in influencing system reliability. Several references explore factors that degrade accuracy but fail to provide specific numerical accuracy data. Reference [103] attributes a 0.25 m error to low depth and distance, but without detailed accuracy metrics, it becomes difficult to compare the performance of this system against others. Reference [104] discusses the impact of signal-to-noise ratio adjustments on accuracy, while [105] points to an increased signal-to-noise ratio as a factor that can enhance accuracy by up to 77%. However, neither study offers specific accuracy numbers, which limits the utility of their findings. Reference [38] addresses the importance of compass calibration and depth sensor accuracy, recognizing their critical role in underwater navigation systems, but again lacks quantitative data. Reference [73] mentions a drift rate in the Inertial Navigation System (INS) as a significant factor in degradation but provides no detailed accuracy statistics, further contributing to the qualitative focus of these studies. Such information is useful for understanding the causes of degradation, but without measurable outcomes, their findings are less impactful. Reference [52] offers an interesting middle ground by providing an accuracy figure of 0.2%, although it does not delve deeply into the causes of degradation or provide error ranges. This study, while providing some numerical data, lacks the context of other influencing factors, making it less comprehensive in comparison to other references. A notable portion of the table includes studies that neither provide detailed accuracy data nor delve into the reasons for accuracy degradation. Papers [16; 27; 29; 32; 39; 59; 62; 69; 79; 91] are examples of this. These studies either focus on other technical aspects of the systems or omit accuracy and degradation discussions altogether. For instance, [79] simply provides a table of accuracies without further elaboration, while [59] discusses component restrictions with out linking them to quantitative accuracy metrics. Other studies, like [20, 87], only mention general factors that could affect accuracy, such as air pressure changes and environmental conditions, but they do not provide detailed information. Such omissions make it difficult to integrate these studies into a broader analysis of underwater system performance.