基于波形結(jié)構(gòu)特征和支持向量機(jī)的水面目標(biāo)識(shí)別
doi: 10.11999/JEIT150139
基金項(xiàng)目:
國(guó)家自然科學(xué)基金(11234002)資助課題
Recognition of Marine Acoustic Target Signals Based on Wave Structure and Support Vector Machine
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摘要: 借鑒語(yǔ)音聲學(xué)的研究成果，音色可作為區(qū)分不同目標(biāo)的依據(jù)。由于艦船輻射噪聲的音色信息包含在其信號(hào)的波形結(jié)構(gòu)特征中，可以通過(guò)提取艦船輻射噪聲的波形結(jié)構(gòu)特征判斷目標(biāo)類型。該文對(duì)水面目標(biāo)信號(hào)時(shí)域波形結(jié)構(gòu)特征提取進(jìn)行了研究，構(gòu)建了基于信號(hào)統(tǒng)計(jì)特性的特征矢量，包括過(guò)零點(diǎn)波長(zhǎng)、峰峰幅度、過(guò)零點(diǎn)波長(zhǎng)差分以及波列面積等。應(yīng)用支持向量機(jī)(Support Vector Machine, SVM)作為分類器識(shí)別兩類水面目標(biāo)信號(hào)，核函數(shù)為徑向基函數(shù)(RBF)。提出了差分進(jìn)化和粒子群算法的混合算法，優(yōu)化了懲罰因子和徑向基函數(shù)參數(shù)的選取，兩類目標(biāo)的識(shí)別率較常規(guī)的網(wǎng)格搜索法有顯著提高。
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關(guān)鍵詞:
- 信號(hào)處理 /
- 水面目標(biāo)識(shí)別 /
- 波形結(jié)構(gòu)特征 /
- 支持向量機(jī) /
- 優(yōu)化算法
Abstract: According to research findings of speech acoustics, the timbre is applied to identify different types of targets. Since the information of timbre is indicated in the wave structure of time series, the feature of wave structure can be?extracted to classify various marine acoustic targets. The method of feature extraction based on wave structure is studied. The nine-dimension feature vector is constructed on the basis of signal statistical characteristics, including zero-crossing wavelength, peek-to-peek amplitude, zero-crossing-wavelength difference, wave train areas and so on. And the Support Vector Machine (SVM) is applied as a classifier for two kinds of marine acoustic target signals. The kernel function is set Radial Basis Function (RBF). The penalty?factor and parameter of RBF are properly selected by the method of combination of Differential Evolution (DE) and Particle Swarm Optimization (PSO), which helps to obtain better recognition rates than the grid search method. -
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