1.空间基准全国重点实验室,陕西 西安,710054
2.国家海洋技术中心漳州基地筹建办公室,福建 厦门,361007
孙文舟,博士,高级工程师,主要从事海洋大地测量方面的研究。1519374228@qq.com
收稿:2024-10-10,
纸质出版:2025-12-05
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孙文舟,朱忆,曾安敏,等.深水目标定位声速剖面自适应分层方法[J].武汉大学学报(信息科学版),2025,50(12):2401-2407.
SUN Wenzhou,ZHU Yi,ZENG Anmin,et al.A Self-Adaptive Layering Method of Sound Velocity Profile for Deep-Water Object Positioning[J].Geomatics and Information Science of Wuhan University,2025,50(12):2401-2407.
孙文舟,朱忆,曾安敏,等.深水目标定位声速剖面自适应分层方法[J].武汉大学学报(信息科学版),2025,50(12):2401-2407. DOI:10.13203/j.whugis20220662
SUN Wenzhou,ZHU Yi,ZENG Anmin,et al.A Self-Adaptive Layering Method of Sound Velocity Profile for Deep-Water Object Positioning[J].Geomatics and Information Science of Wuhan University,2025,50(12):2401-2407. DOI:10.13203/j.whugis20220662
针对高精度水下目标定位声线跟踪法计算效率低的问题,提出一种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、减少声速剖面的层数来降低计算量。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;然后,按照声速梯度垂向变化规律进行结构化分层,在此基础上,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,采用中国南海实测声速剖面数据对所提算法进行了验证。与10 m等间隔分层方法对比,所提方法在分层数量减少了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毫米级。
Objectives
2
Acoustic ray-tracing method is an important means to solve the problem of acoustic ray bending in the process of propagation. This method calculates the slant range in deep-water positioning and can effectively minimize errors from the acoustic ranging system. However
the accompanying problem causes the reduction of computational efficiency. To solve this problem
this paper proposes a self-adaptive layering method based on the area difference of sound velocity profile (SVP)
which reduces the computational cost by optimizing the layering strategy of SVP.
Methods
2
First
the relationship between the SVP area difference and ranging error is established according to the corresponding research. Based on this relationship
the constant-gradient and the zero-gradient ray-tracing method are analyzed
which is more suitable for slant range calculation. And the maximum tolerance of SVP area difference is obtained by setting the maximum tolerance of ranging error. Then
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
2
The results show that the measured SVP in the same sea area and during a similar time can be considered as the same cluster SVP
which satisfies the inear relationship between SVP area and propagation time. The average value of multiple measured SVPs can be approximately considered as the background SVP to estimate the linear coefficient. The adaptive layering method can optimize the layering scheme according to the changing law of SVP curve. The layering interval increases when the gradient change rate is small
and reduces when 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. Compared with equally spaced layering of 10 m
when the number of layering is reduced by 86%
the ranging error caused by layering reduces from centimeter level to millimeter level
which proves the effectiveness of the proposed method.
Conclusions
2
The adaptive method has strong robustness and practicability. It can adjust the layering strategy according to the structural characteristics of SVP and the usage scenarios of offshore operation. Since the number of SVP layers is greatly reduced
the calculation speed is greatly improved. It will be helpful for large amount of data process or real-time underwater acoustic navigation.
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