文章摘要
荆丹翔,周晗昀,韩军,张进.基于成像声呐DIDSON的水域内鱼群数量估计方法*[J].,2019,38(4):705-711
基于成像声呐DIDSON的水域内鱼群数量估计方法*
Fish abundance estimation based on an imaging sonar
投稿时间:2019-02-10  修订日期:2019-06-30
中文摘要:
      为准确估计整片水域中的鱼群数量,提出一种利用成像声呐进行数量估计的方法。将成像声呐固定在调查船下,并使波束发射方向与船前进方向一致,通过走航调查方式采集水下信息,对采集的数据进行声呐图像构建、噪声去除、目标提取,其中噪声去除采用固定数据窗口的迭代最小二乘法,目标提取采用基于三倍标准差准则的阈值分割法。接着利用扩展卡尔曼滤波结合最近邻的多目标跟踪算法对图像中的个体目标进行一一计数,同时统计声呐扫描过的水域面积,获得目标个数的平均面密度值,最后结合水域占地面积,估算出整片水域中的鱼群数量。利用该方法实现对滴水湖鱼群数量的估计,通过与人工计数结果比较,发现基于声呐图像处理的数量统计方法具有较高精度,两者的统计值相差约10%。
英文摘要:
      In order to estimate the fish abundance accurately in a body of water, a method of fish quantity estimation using an imaging sonar is proposed. The imaging sonar is fixed under the survey ship, making the beam lunching direction the same with the ship’s moving direction, and sonar data is collected by means of the investigation on navigation. The image reconstruction, noise reduction and target extraction are conducted in turn. Fixed data window recursive least squares (FDWRLS) algorithm is adopted to reduce the speckle noise in sonar images, and threshold segmentation method based on thrice standard error principle is utilized to extract multiple targets. Therefore, multiple fish targets can be tracked using the nearest neighbor (NN) algorithm combined with extended Kalman filtering (EKF) and the targets are counted one by one. Meanwhile, the area detected by the sonar is added together to obtain the average areal density of fish. Finally, the fish abundance in this body of water is estimated with the parameter of water area. A field experiment is conducted in Dishui Lake to validate the effectiveness of the proposed method. Manual counting results of two datasets picked up from the sonar data are compared with the ones by the proposed method, it is shown that the fish abundance estimation method based on sonar image processing provides a higher accuracy rate, and the deviation between them is approximately 10%.
DOI:10.11684/j.issn.1000-310X.2019.04.030
中文关键词: 成像声呐,数量估计,噪声去除,目标提取,目标跟踪
英文关键词: imaging sonar, abundance estimation, noise reduction, target extraction, target tracking
基金项目:浙江省自然科学基金
作者单位E-mail
荆丹翔 浙江大学 jingdxiang@zju.edu.cn 
周晗昀 浙江大学 11634017@zju.edu.cn 
韩军 浙江大学 jhan@zju.edu.cn 
张进 上海海洋大学 j_zhang@shou.edu.cn 
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