| 基于Echoview声学数据后处理系统的背景噪声扣除方法 |
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| 作者姓名： | 张俊 陈丕茂 陈国宝 于杰 范江涛 邱永松 |
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| 作者单位： | [1]农业部南海渔业资源环境重点野外科学观测试验站,广州510300 [2]中国水产科学研究院南海水产研究所,广州510300 |
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| 基金项目： | 农业部南海渔业资源环境重点野外科学观测试验站人工鱼礁学科建设专项开放课题项目（2011-2012）、国家财政专项项目“南海海洋捕捞信息动态采集网络（2009-2012）”、中央级公益性科研院所基本科研业务费专项资金（2013ZD03;2014TS18）、国家科技支撑计划项目（2013BAD13B06）和农业部财政专项项目（NFZX2013）共同资助 |
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| 摘 要： | 基于2012年2~3月南海中部鱼类资源声学调查资料,利用Echoview系统中虚拟变量模块的功能,探讨扣除背景噪声对声学映像、单脉冲回声信号图、海里面积散射系数(NASC)和体积反向散射强度(Sv)的影响。结果显示,背景噪声对120kHz数据的干扰明显强于38kHz;随着水深逐渐增加,扣除背景噪声后,120kHz声学映像变化亦比38kHz更加明显;扣除背景噪声时,换能器表面1m处的Sv值在不断改变过程中,相同水层中不同频率数据的NASC和Sv的变化差异明显,其差异程度因具体水层而异,相同频率数据在不同水层的NASC和Sv的变化差异亦明显。分析认为,扣除背景噪声非常必要;本研究的方法能够较好地排除背景噪声,是提高资源评估准确度的有效手段。
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| 关 键 词： | 回声积分 时变增益 背景噪声消除 虚拟变量法 |
| 收稿时间： | 2012/12/30 0:00:00 |
| 修稿时间： | 2013/6/13 0:00:00 |
Study on background noise removal based on Echoview acoustic data post-processing system |
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| Authors: | ZHANG-Jun CHEN Pi-mao CHEN Guo-bo YU Jie FAN Jiang-tao and QIU Yong-song |
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| Institution: | 1 Key Field Scientific Experimental Station of South China Sea Fishery Resource and Environment, Ministry of Agriculture Guangzhou 510300) ( South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300) |
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| Abstract: | ABSTRACT Based on the data from fishery resource acoustic surveys in central South China Sea from February to March 2012, using Virtual Variable Module of Echoview system, the effects of subtracting background noise on echogram, Ping echogram, nautical area scattering coefficient （NASC） and volume backscattering strength （Sv） were investigated. The results showed that the interference of background noise on 120 kHz transducer was much stronger than that on 38 kHz transducer. After subtracting background noise, the variation of echogramfrom 120 kHz transducer was much more obvious than that from 38 kHz as the depth range in- creases; as the Sv, at 1 m to the transducer surface （S v1 m for short） changed, the variation of NASC and Sv differentiated obviously between frequencies in the same depth layer and the ex- tent of variation was dependent on depth layers, and the variation of NASC and Sv from the transducer of the same frequency differentiated obviously between depth layers too. The distin- guishing features of variation of NASC and Sv were important bases for determining Sv1m. According to the analysis, it was absolutely essential to remove background noise in the post-pro cessing of fishery acoustic data; background noise could be removed well by this method, which was a valid means of enhancing accuracy of acoustic stock estimation. |
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| Keywords: | Echo-integration Time Varied Gain （TVG） Background noise subtraction Virtual variable method |
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