兵工学报
兵工學報
병공학보
ACTA ARMAMENTARII
2009年
7期
935-939
,共5页
信息处理技术%线谱%水声信号处理%信号检测
信息處理技術%線譜%水聲信號處理%信號檢測
신식처리기술%선보%수성신호처리%신호검측
information processing technique%line spectrum%underwater acoustical signal processing%signal detection
舰船辐射声中的低频线谱是舰船的一个重要特征量,对声引信的信号检测、识别与分类具有重要的作用.随着现代舰船,特别是潜艇声辐射能量迅速降低和海洋环境噪声级逐年增加,利用舰船噪声中线谱信号对目标的发现距离正在减小.本文利用双树复解析小波变换(DT-CWT)对海洋环境噪声和舰船噪声线谱信号进行小波分解,并对小波系数的层间联合分布进行分析,建立了海洋环境噪声和线谱信号的小波系数的层间联合分布的数学模型,并推导出最大后验概率估计子(MAP)的解析表达式,用于去除噪声干扰,检测淹没在海洋噪声背景中的舰船噪声线谱信号.对实测舰船噪声信号和海洋环境噪声的分析表明,所提出的算法能够明显减弱连续谱干扰成分,提高舰船噪声中线谱信号的检测效果.
艦船輻射聲中的低頻線譜是艦船的一箇重要特徵量,對聲引信的信號檢測、識彆與分類具有重要的作用.隨著現代艦船,特彆是潛艇聲輻射能量迅速降低和海洋環境譟聲級逐年增加,利用艦船譟聲中線譜信號對目標的髮現距離正在減小.本文利用雙樹複解析小波變換(DT-CWT)對海洋環境譟聲和艦船譟聲線譜信號進行小波分解,併對小波繫數的層間聯閤分佈進行分析,建立瞭海洋環境譟聲和線譜信號的小波繫數的層間聯閤分佈的數學模型,併推導齣最大後驗概率估計子(MAP)的解析錶達式,用于去除譟聲榦擾,檢測淹沒在海洋譟聲揹景中的艦船譟聲線譜信號.對實測艦船譟聲信號和海洋環境譟聲的分析錶明,所提齣的算法能夠明顯減弱連續譜榦擾成分,提高艦船譟聲中線譜信號的檢測效果.
함선복사성중적저빈선보시함선적일개중요특정량,대성인신적신호검측、식별여분류구유중요적작용.수착현대함선,특별시잠정성복사능량신속강저화해양배경조성급축년증가,이용함선조성중선보신호대목표적발현거리정재감소.본문이용쌍수복해석소파변환(DT-CWT)대해양배경조성화함선조성선보신호진행소파분해,병대소파계수적층간연합분포진행분석,건립료해양배경조성화선보신호적소파계수적층간연합분포적수학모형,병추도출최대후험개솔고계자(MAP)적해석표체식,용우거제조성간우,검측엄몰재해양조성배경중적함선조성선보신호.대실측함선조성신호화해양배경조성적분석표명,소제출적산법능구명현감약련속보간우성분,제고함선조성중선보신호적검측효과.
The low-frequency line spectrum of ship-radiated noise is an important characteristic quantity which plays an important part in the signal detection, recognition and classification of acoustical fuze. With the decreasing of ship, especially submarine radiated acoustic energy and the increasing of ambient noise in the sea, the distance to detect targets based on using the line spectrum signal is getting shorter and shorter year by year. In order to denoise and detect the ship's line spectrum signal submerged in ocean noise, a mathematic model of inter-scale joint distribution of wavelet coefficients for the noise and the signal was established, and an analytical expression of the maximum a posteriori (MAP) was deduced, on the basis of decomposing the noise and the signal by the dual tree complex wavelet transform (DT-CWT) and analyzing the inter-scale joint distribution of wavelet coefficients. The denoised results show that the proposed algorithm can evidently weaken the continuous spectrum disturbance component and improve detecting effect of the ship's line spectrum signal.