数字海洋与水下攻防2025，Vol.8Issue(2)：110-116,7.DOI:10.19838/j.issn.2096-5753.2025.02.001
水下航行器仿生流场感知方法研究
Study on Biomimetic Flow Field Sensing Method of Underwater Vehicles
摘要
Abstract
Accurately identifying the angle of attack and speed of underwater vehicles relative to ocean currents holds significant importance for various operations.These include motion control of underwater vehicles in complex ocean current environments,identification of launch windows for underwater weapons,and the perception and warning of internal ocean waves.This paper uses the Suboff submarine model as the research subject to investigate methods for identifying the angle of attack and speed of underwater vehicles relative to ocean currents based on the principle of biomimetic flow field perception.Initially,Computational Fluid Dynamics(CFD)and potential flow simulation models are established to study the flow fields surrounding underwater vehicles.It is discovered that for predicting unsteady pressure at the bow of underwater vehicles,the results from CFD and potential flow simulations are very similar.Consequently,it is feasible to use the potential flow model to quickly and accurately predict the bow pressure of underwater vehicles at high angles of attack.Then,a flow field parameter identification model for underwater vehicles is developed by integrating potential flow theory with Kalman filtering.Both simulation and experimental results demonstrate that the flow field parameter identification model can achieve an identification error within 3 degrees for the angle of attack across a range of±80 degrees,and the relative error for speed recognition is within 5%.关键词
流场感知/水下航行器/势流/卡尔曼滤波Key words
flow field sensing/underwater vehicles/potential flow/Kalman filter分类
交通运输引用本文复制引用
徐文华,许国冬,焦甲龙..水下航行器仿生流场感知方法研究[J].数字海洋与水下攻防,2025,8(2):110-116,7.基金项目
国家自然科学基金"基于仿鱼侧线的潜航器非定常外流场感知方法研究"(52401378) （52401378）
水动力学全国重点实验室开放基金"基于分布式压力数据的水下无人潜航器发射窗口识别方法"(JCKY2023201CA0201) （JCKY2023201CA0201）
广东省自然科学基金"仿生鱼编队推进的涡流场智能感知研究"(2023A1515111122) （2023A1515111122）
广东省自然科学基金"仿鱼侧线涡流智能感知与重构模型及其在仿生鱼尾迹追踪中的应用"(2024A1515012646). （2024A1515012646）
