水下无人航行器（Unmanned Underwater Vehicle，UUV）能够在复杂的海洋环境下作业，通过雷达、声呐和水下摄像头等传感设备收集海洋环境数据，包括海流、内波、中尺度涡、密度跃层和航行障碍等。海洋环境数据的正确与否直接影响着UUV的安全，然而海洋环境数据具有多源、多态、异构的特点，难以有效整合。栅格化方法能够将地理空间划分成规则的格网，以矩阵的形式储存、表达并处理多元化的数据，在数据整理方面得到了广泛应用。因此，本文基于栅格化方法提出了一套栅格划分规则和栅格要素更新机制。在此基础上，建立了声场模型、UUV目标强度模型和UUV辐射噪声模型，形成了UUV隐蔽性综合判断方法，用敌方目标声呐探测范围和UUV暴露概率表征UUV的隐蔽性。最后，以仿真实验的形式证明了方法的有效性。
Unmanned underwater vehicles can operate in complex marine environments, collecting marine environmental data, including ocean currents, internal waves, mesoscale eddies, density layers, and navigational obstacles, through sensing devices such as radar, sonar, and underwater cameras. The accuracy of marine environmental data directly impacts the safety of UUVs; however, marine environmental data is characterized by being multi-source, polymorphic, and heterogeneous, making effective integration challenging. The rasterization method can partition geographic space into regular grids, storing, expressing, and processing diverse data in matrix form, which has been widely applied in data organization. Therefore, based on the rasterization method, this paper proposes a set of raster division rules and a raster element update mechanism. On this basis, the sound field model, the UUVs target strength model and the UUVs radiated noise model are established. Eventually, a comprehensive judgment method for the stealthiness of UUVs is formed. The stealthiness of UUVs is characterized by the detection range of the enemy’s sonar and the exposure probability curve of UUVs. Finally, the effectiveness of the proposed method is demonstrated through simulation experiments.
2025,47(23): 113-117 收稿日期：2025-3-14
DOI：10.3404/j.issn.1672-7649.2025.23.017
分类号：U675.7
作者简介：尹洪亮(1984-),男,研究员,研究方向为潜艇总体、无人系统技术
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