This paper proposes a method for passive detection of autonomous underwater vehicle (AUV) wakes using a cilium-inspired wake sensor (CIWS), which can be used for the detection and tracking of AUVs. First, the characteristics of the CIWS and its working principle for detecting underwater flow fields are introduced. Then, a flow velocity sensor is used to measure the flow velocities of the “TS MINI” AUV’s wake at different positions, and a velocity field model of the “TS MINI” AUV’s wake is established. Finally, the wake field of the “TS MINI” AUV was measured at various positions using the CIWS. By analyzing the data, the characteristic frequency of the AUV’s propeller is identified, which is correlated with the AUV’s rotation speed and the number of blades. Through further analysis, a mapping model is established between the spectral amplitude of the characteristic frequency at different positions and the corresponding wake velocity. By substituting this mapping model into the AUV’s wake velocity field model, the possible position range of the sensor relative to the AUV propeller can be estimated. The research provides a technical foundation for underwater detection and tracking missions based on wake detection.

This study introduces a bionic vector wake sensor utilizing micro electro mechanical system (MEMS) technology to facilitate flow field sensing and the coordinated formation of autonomous underwater vehicles (AUVs). Inspired by the lateral line system of fish, the sensor incorporates a piezoresistive transducer featuring a bionic cilia and double-supported beam configuration. Drawing from the hierarchical fluid mechanism of the neural mound in blind cave fish, the sensor's design optimizes a composite package featuring a star-shaped package structure using finite-element method (FEM). Experimental results demonstrate the sensor's high sensitivity and ability to discern vectors. In multi-AUV platform formation tests, the sensor reliably detects wake turbulence from a leading target, showcasing its practicality and potential for engineering applications in complex flow environments.