【摘要】 针对水下无人平台低噪声高灵敏探测需求,本文提出基于目标频谱特征信息的谐振敏感检测思想。利用水听器在谐振频率处具有高灵敏的特点,根据水下目标的频域特征信息设计水听器敏感结构。本文研制了谐振敏感式压电微机电系统芯片和水听器样机,并进行了实验测试。所设计水听器样机在谐振频率处实现了高灵敏响应(-146d B@12k Hz(Re.1V/μPa)和-138d B@4k Hz(Re.1V/μPa))和远低于knudsen零级海况的自噪声水平(M5#样机在谐振频率处等效噪声声压谱密度级22.03d B@4k Hz■)。本文所提出的基于目标特征信息的谐振敏感检测思想为水下目标检测提供了思路。更多还原

【Abstract】 To address the low-power consumption and detection requirements for equipment carried by underwater unmanned platforms. This work proposes the idea of resonant sensitive detection based on target spectral features; that is, the sensitive structure of a hydrophone is designed, leveraging the high sensitivity of hydrophones at the resonant frequency, based on the frequency domain characteristics of underwater targets. Building upon this idea, several piezoelectric MEMS resonant sensitive chips and characteristic sound pressure hydrophones for target frequency domain feature information were designed and developed, and experimental tests were conducted. Sound pressure hydrophone prototypes M3 and M5 achieved high sensitivity responses at their resonant frequencies of-146 dB@12 kHz(Re.1V/μPa)和-138 dB@4 kHz(Re.1V/μPa). These prototypes exhibited self-noise levels far below the Knudsen sea state zero noise levels at the resonant frequency: the equivalent noise spectral density level of M5 prototypes at the resonant frequency was 22.03 dB@4 kHz(Re.■ ). The proposed concept of resonance-sensitive detection based on target feature information provides a new approach for underwater target detection.更多还原