水下高速目標(biāo)聲譜圖特征提取及分類(lèi)設(shè)計(jì)
doi: 10.11999/JEIT170283
-
1.
(海軍潛艇學(xué)院 青島 266000) ②(中國(guó)人民解放軍31001部隊(duì) 北京 100094)
Feature Extraction and Classification of Spectrum of Radiated Noise of Underwater High Speed Vehicle
-
1.
(Navy Submarine Academy, Qingdao 266000, China)
-
2.
(PLA 31001, Beijing 100094, China)
-
摘要: 為了增加水下高速目標(biāo)的識(shí)別特征維度,優(yōu)化識(shí)別效果,該文設(shè)計(jì)了一種基于目標(biāo)輻射噪聲高速特征量(High Speed Characteristic Quantity, HSCQ)的分類(lèi)方法。首先,針對(duì)水下高速目標(biāo)輻射噪聲的DEMON(Detection of Envelope Modulation On Noise)譜特征進(jìn)行分析,根據(jù)DEMON譜的頻率可分性,定義了DEMON譜調(diào)制分布比(Modulation Distribution Ratio, MDR)。然后,根據(jù)水下高速目標(biāo)輻射噪聲的功率譜歷程圖直紋特征,應(yīng)用圖像邊緣檢測(cè)、線譜生長(zhǎng)等理論進(jìn)行特征提取,并分析了功率譜歷程圖的直紋特征量(Straight-line Characteristic Quantity of Spectrum, SCQS)。最后,根據(jù)2種特征量的實(shí)測(cè)信號(hào)分析結(jié)果,定義了目標(biāo)輻射噪聲的HSCQ,實(shí)現(xiàn)了一種新的水下高速目標(biāo)分類(lèi)方法。實(shí)測(cè)信號(hào)分析結(jié)果顯示,采用MDR或SCQS進(jìn)行單特征量分類(lèi),非高速目標(biāo)的誤報(bào)率分別為21.4%和16.3%;采用HSCQ進(jìn)行分類(lèi),非高速目標(biāo)的誤報(bào)率僅為4.1%。
-
關(guān)鍵詞:
- 水下高速目標(biāo) /
- 聲譜圖 /
- 調(diào)制分布比 /
- 直紋特征量
Abstract: In order to improve the result of underwater high speed vehicle classification, a classification method that is based on High Speed Characteristic Quantity (HSCQ) of vehicle radiated noise is designed. Firstly, analysis of Detection of Envelope Modulation On Noise (DEMON) spectrum of actual measured radiated noise is finished. The Modulation Distribution Ratio (MDR) of radiated noise is defined based on the separability of modulation frequency of DEMON spectrum. Then the spectrograms feature analysis and feature extraction of underwater high speed radiated noise are done based on image edge detection and edge growing. The Straight-line Characteristic Quantity of Spectrum (SCQS) of vehicle radiated noise is analyzed. Finally, considering the analysis results of two types of characteristic quantity, a new classification method of underwater high speed vehicle is realized and HSCQ of vehicle radiated noise is designed. The actual measured radiated noise analysis shows that, the false alarm rate of non-high speed vehicle is respectively 21.4% (only using MDR), 16.3% (only using SCQS), and 4.1% (using HSCQ). -
YU Yue, SUN Zhenxin, and CHEN Yanhui. Guidance type identification based on cumulative azimuth variation of incoming torpedo[J]. Fire Control Command Control, 2015, 40(10): 87-89. 余躍, 孫振新, 陳顏輝. 基于累積方位變化量的來(lái)襲魚(yú)雷制導(dǎo)方式識(shí)別[J]. 火力與指揮控制, 2015, 40(10): 87-89. 孫向前, 范展, 李晴. 一種基于相關(guān)積分的互譜WVD目標(biāo)方位估計(jì)方法[J]. 聲學(xué)技術(shù), 2015, 34(1): 23-28. doi: 10.16300/ j.cnki.1000-3630.2015.01.005. SUN Xiangqian, FAN Zhan, and LI Qing. A method of target DOA estimation based on correlation integral and cross spectrum WVD[J]. Technical Acoustics, 2015, 34(1): 23-28. doi: 10.16300/j.cnki.1000-3630.2015.01.005. 周殿寶, 張奎, 易紅. 水下高速航行體的航向角和距離估計(jì)方法[J]. 魚(yú)雷技術(shù), 2007, 15(1): 38-41. ZHOU Dianbao, ZHANG Kui, and YI Hong. Estimation of course angle and distance for high speed underwater vehicles[J]. Torpedo Technology, 2007, 15(1): 38-41. 孫常存, 邢國(guó)強(qiáng), 曲兆宇. 一種水下高速小目標(biāo)的多普勒頻率估計(jì)方法[J]. 艦船電子工程, 2015, 35(10): 162-165. doi: 10.3969/j.issn.1672-9730.2015.10.041. SUN Changcun, XING Guoqiang, and QU Zhaoyu. Doppler frequency estimation method of underwater high-speed small target[J]. Ship Electronic Engineering, 2015, 35(10): 162-165. doi: 10.3969/j.issn.1672-9730.2015.10.041. 李海濤, 程玉勝, 戴衛(wèi)國(guó), 等. 小波包分形與支持向量機(jī)在水聲目標(biāo)識(shí)別中的應(yīng)用研究[J]. 聲學(xué)技術(shù), 2015, 34(3): 219-222. doi: 10.3969/j.issn.1000-3630.2015.03.006. LI Haitao, CHENG Yusheng, DAI Weiguo, et al. A method based on wavelet fractal and support vector machine for underwater target recognition[J]. Technical Acoustics, 2015, 34(3): 219-222. doi: 10.3969/j.issn.1000-3630.2015.03.006. 吳姚振, 楊益新, 楊龍, 等. 基于恒定束寬波形保真及干擾抑制的水下目標(biāo)識(shí)別方法[J]. 西北工業(yè)大學(xué)學(xué)報(bào), 2015, 33(5): 843-848. WU Yaozhen, YANG Yixin, YANG Long, et al. Underwater target recognition based on constant-beamwidth waveform fidelity and interference-suppression[J]. Journal of Northwestern Polytechnical University, 2015, 33(5): 843-848. 吳國(guó)清, 王美剛, 陳耀明. 水聲波導(dǎo)中包絡(luò)線譜強(qiáng)度數(shù)值預(yù)報(bào)[J]. 聲學(xué)學(xué)報(bào), 2013, 37(4): 432-439. WU Guoqing, WANG Meigang, and CHEN Yaoming. Numerical prediction of envelope line spectrum intensity in underwater acoustic waveguide[J]. Acta Acustica, 2013, 37(4): 432-439. 文洪濤, 楊燕明, 周鴻濤, 等. 海洋水下聲探測(cè)信號(hào)的分類(lèi)與分析[J]. 應(yīng)用海洋學(xué)學(xué)報(bào), 2015, 34(2): 272-278. doi: 10.3936/ j.issn.2095-4972.2015.02.017. WEN Hongtao, YANG Yanming, ZHOU Hongtao, et al. Classification and analysis on the ocean underwater acoustic detection signals[J]. Journal of Applied Oceanography, 2015, 34(2): 272-278. doi: 10.3936/j.issn.2095-4972.2015.02.017. 黃文斌, 陳顏輝, 薛昌友. 來(lái)襲魚(yú)雷類(lèi)型識(shí)別指標(biāo)提取與算法設(shè)計(jì)[J]. 南京理工大學(xué)學(xué)報(bào), 2011, 35(2): 199-203. HUANG Wenbin, CHEN Yanhui, and XUE Changyou. Indices extraction and algorithm design for recognizing type of incoming torpedo[J]. Journal of Nanjing University of Science and Technology, 2011, 35(2): 199-203. 江向東. 水下高速目標(biāo)多傳感器聯(lián)合譜特征分布識(shí)別方法[J]. 艦船科學(xué)技術(shù), 2012, 34(4): 86-88. doi: 10.3404/j.issn.1672- 7649.2012.04.020. JIANG Xiangdong. Line spectrum distribute based high speed underwater vehicle classification method[J]. Ship Science and Technology, 2012, 34(4): 86-88. doi: 10.3404/ j.issn.1672-7649.2012.04.020. 王森, 高鑫, 程玉勝. 基于調(diào)制統(tǒng)計(jì)量的水下高速目標(biāo)分類(lèi)算法[J]. 聲學(xué)技術(shù), 2014, 33(1): 61-64. doi: 10.3969/j.issn.1000- 3630.2014.01.013. WANG Sen, GAO Xin, and CHENG Yusheng. A classification method of high speed underwater vehicle based on modulation statistics[J]. Technical Acoustics, 2014, 33(1): 61-64. doi: 10.3969/j.issn.1000-3630.2014.01.013. 海深, 王森. 邊緣檢測(cè)結(jié)合高斯平滑的魚(yú)雷聲譜圖識(shí)別方法[J]. 計(jì)算機(jī)工程與應(yīng)用, 2017, 53(3): 160-163. doi: 10.3778/ j.issn.1002-8331.1506-0021. HAI Shen and WANG Sen. Combination of Gaussian smoothing and edge detection of torpedo spectrum recognition method[J]. Computer Engineering and Applications, 2017, 53(3): 160-163. doi: 10.3778/j.issn.1002- 8331.1506-0021. 弓彥婷, 程小雪, 任洪梅, 等. 聲譜圖顯著性在音頻識(shí)別中的應(yīng)用[J]. 合肥工業(yè)大學(xué)學(xué)報(bào)(自然科學(xué)版), 2016, 39(1): 62-66. GONG Yanting, CHENG Xiaoxue, REN Hongmei, et al. Application of the saliency of spectrogram in audio recognition[J]. Journal of Hefei University of Technology, 2016, 39(1): 62-66. SONG J, YANG Y, HUANG Z, et al. Effective multiple feature hashing for large-scale near-duplicate video retrieval[J]. IEEE Transactions on Multimedia, 2013, 15(8): 1997-2008. 馬理想, 曾向陽(yáng). 一種視聽(tīng)融合的水下目標(biāo)識(shí)別方法研究[J]. 聲學(xué)技術(shù), 2015, 34(3): 209-213. doi: 10.3969/j.issn.1000- 3630.2015.03.004. MA Lixiang and ZENG Xiangyang. Study of underwater targets recognition based on audiovisual feature integration [J]. Technical Acoustics, 2015, 34(3): 209-213. doi: 10.3969/ j.issn.1000-3630.2015.03.004. WU Y, YANG Y, TIAN F, et al. Robust target feature extraction based on modified cochlear filter analysis model[C]. IEEE International Conference on Signal Processing, Kunming, China, 2013: 1-5. 石美紅, 李青, 趙雪青, 等. 一種基于保角相位的圖像邊緣檢測(cè)新方法[J]. 電子與信息學(xué)報(bào), 2015, 37(11): 2594-2600. doi: 10.11999/JEIT150364. SHI Meihong, LI Qing, and ZHAO Xueqing, et al. A new approach for image edge detection based on conformal phase[J]. Journal of Electronics Information Technology, 2015, 37(11): 2594-2600. doi: 10.11999/JEIT150364. WONG Y P, SOH V C M, BAN K W, et al. Improved canny edges using ant colony optimization[C]. The Fifth International Conference on Computer Graphics, Imaging and Visualization, Penang, 2008: 197-202. -
計(jì)量
- 文章訪問(wèn)數(shù): 1349
- HTML全文瀏覽量: 158
- PDF下載量: 272
- 被引次數(shù): 0