A self-adaptive layering method of the sound velocity profile for deep-water object positioning
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摘要: 针对高精度水下目标定位声线跟踪法计算效率低的问题。本文提出了基于声速剖面面积差的自适应分层方法，通过优化声速剖面分层策略，减小分层数的思路降低计算量。首先，根据声线跟踪法计算斜距值时传播时间与声速剖面面积差近似线性负相关的关系，确定了声速剖面面积差与测距误差的关系，通过设置测距误差最大容许值得到声速剖面面积差的最大容许值；其次，先按照声速梯度垂向变化规律进行结构化分层，然后在此基础上，再以声速剖面面积差的最大容许值作为约束条件进行自适应分层。最后，用南海实测声速剖面数据对算法进行验证，与10m等间隔分层方法对比，计算效率提高了86%的情况下因声速剖面简化引入的测距误差从厘米级降低到了毫米级。Abstract: Objectives: Acoustic ray-tracing method is an important means to solve the problem of acoustic ray bending in the process of propagation. It was used to calculate the slant range of deep-water object positioning can effectively attenuating the influence of acoustic ranging system error. However, the accompanying problem is the reduction of computational efficiency. To solve this problem, we put forward a self-adaptive layering method based on the area difference of sound velocity profile (SVP), which reduces the computation by optimizing the layering strategy of the SVP. Methods: Firstly, the relationship between the SVP area difference and ranging error is established according to the research of thirteenth reference. Based on this relationship, the constant-gradient and the zero-gradient ray-tracing method were analyzed which is more suitable for slant range calculation. And the maximum tolerance of the SVP area difference is obtained by setting the maximum tolerance of ranging error. Secondly, the structural layering is carried out according to the change law of sound velocity gradient, and the refined layering is carried out on constraint of the maximum tolerance of SVP area difference. Results: The results show that: (1) The measured SVP in the same sea area and during a similar time can be considered as the same cluster SVP, which satisfies the Eq. (1). The average value of multiple measured SVPs can be approximately considered as the background SVP to estimate the linear coefficient k0. (2) The adaptive layering method can optimize the layering scheme according to the changing law of the SVP curve. The layering interval will increase where the gradient change rate is small and reduce the layering interval where the gradient change rate is large, so as to reduce the number of layers as much as possible under the condition of meeting the maximum tolerance ranging error. (3) Compared with equally spaced layering 10m, when the number of layering is reduced by 86%, the ranging error caused by layering is lowered from centimeter level to millimeter level, which proves the effectiveness of this method. Conclusions: The adaptive method has strong robustness and practicability. It can adjust the layering strategy according to the structural characteristics of SVP and usage scenarios of the offshore operation. Since the number of layers of the SVP is greatly reduced, the calculation speed is greatly improved. This will be helpful for large amount of data process or real-time underwater acoustic navigation.
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