舰船轴频电场弱信号高增益检测方法OA
High-Sensitivity Detection Method for Weak Signals of Vessel Shaft-Rate Electric Field
针对舰船轴频电场信号弱且易被噪声掩盖的问题,提出了一种基于优先检测与选择性增强原则的高增益弱信号综合检测方法.首先利用自适应噪声完备集合经验模态分解结合窄带功率谱能量峰值熵比特征,再通过滑动窗口与动态门限技术实现对目标信号的初步检测;信号检测成功后,触发三稳态随机共振与变步长最小平均p范数增强机制,进一步增强目标信号的线谱特征,并在此基础上实现目标信号特征频率的提取.仿真结果表明,所提方法在信噪比为-12 dB的条件下检测准确率超过 85%,漏检率低于 30%,且能准确提取到目标信号的特征频率,为舰船弱电场信号的实时监测提供了可行的技术方案.
There are weak signals in shaft-rate electric fields from vessels,and they are easily masked by noise.To address these issues,this paper proposed a comprehensive high-gain weak signal detection method guided by the priority detection and selective enhancement principle.First,complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)was combined with narrowband power spectrum energy peak entropy ratio(EPER)features.Then,sliding window and dynamic threshold techniques were used to detect the target signal.After successful detection,the proposed method triggered a tri-stable stochastic resonance and variable step-size least mean p-norm(VSS-LMP)enhancement mechanism to further enhance the spectral characteristics of the target signal,thereby enabling the extraction of the target signal's characteristic frequency.Simulation results show that the proposed method achieves a detection accuracy rate exceeding 85%under a signal-to-noise ratio of-12 dB,with a false detection rate below 30%,and it can accurately extract the target signal's characteristic frequency,providing a feasible technical approach for real-time monitoring of weak electric field signals from vessels.
余平洋;王宏磊;杨益新
西北工业大学 航海学院,陕西 西安,710129西北工业大学 航海学院,陕西 西安,710129西北工业大学 航海学院,陕西 西安,710129
军事科技
舰船轴频电场弱信号检测最小平均p范数能量峰值熵比
vesselshaft-rate electric fieldweak signal detectionleast mean p-normenergy peak entropy ratio
《水下无人系统学报》 2026 (1)
29-36,8
国家自然科学基金联合基金重点支持项目资助(U2341201)国家自然科学基金面上项目资助(52271350)基础产品创新科研项目资助(14520208040).
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