水声被动目标识别是水声信号处理领域的重要组成部分,其中弱目标特征检测是目前研究的重点.线谱特征具有稳定性高、物理意义清晰以及时不变性较强等优势,受到学者广泛关注.针对弱目标线谱检测问题,研究基于相位信息的线谱增强方法.首先分析线谱与噪声的相位起伏规律差异,其次研究基于起伏规律的相位加权因子,最后对低频分析与记录(Low Frequency Analysis and Recording,LOFAR)谱进行加权,完成线谱增强.仿真结果表明,该方法能够有效抑制背景噪声,增强线谱输出信噪比,提高线谱特征检测性能.
An Optimized Method for Line Spectrum Detection
Passive underwater target recognition is an important component of underwater signal processing,with weak target feature detection being the current focus of research.The line spectrum features have advantages such as high stability,clear physical meaning,and strong temporal invariance,and have received widespread attention from scholars.Research on line spectrum enhancement methods based on phase information for weak target line spectrum detection.Firstly,analyze the difference in phase fluctuation patterns between line spectrum and noise.Secondly,study the phase weighting factor based on fluctuation patterns.Finally,weight the Low Frequency Analysis and Recording(LOFAR)spectrum to complete line spectrum enhancement.The simulation results show that this method can effectively suppress background noise,enhance the signal-to-noise ratio of line spectrum output,and improve the performance of line spectrum feature detection.
line spectrum detectionphase fluctuation characteristicsunderwater acoustic signal
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