基于成像声呐的鱼类三维空间分布
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摘要
针对海洋牧场中鱼群的三维空间分布问题,本研究提出一种利用成像声呐进行位置计算的方法。将成像声呐固定在船舷外侧的水下,并保证波束发射方向和声呐移动方向一致,通过走航的方式采集水下鱼群信息。首先对采集的原始数据进行图像处理,包括图像构建、背景去除、目标提取等,然后利用基于交互式多模型联合概率数据关联算法对水下目标进行关联处理,得到同一个目标在声呐水平视场中不同帧图像中的对应关系,在此基础上根据连续两帧图像中目标位置关系计算目标的空间坐标,最后结合关联算法获得多目标在三维空间中的运动轨迹以及深度分布情况。研究表明,本方法可以有效获取鱼群在水下的三维运动轨迹及其分布情况,这将为鱼类行为分析以及海洋牧场的资源评估提供技术支持。
In order to obtain the three-dimensional(3 D) distribution of fish in a marine ranching, a method using imaging sonar to calculate the 3 D coordinates of fish is proposed in this paper. The imaging sonar used in this research is a Dual-frequency Identification sonar(DIDSON). It is a multi-beam sonar that uses acoustic lens to form individual beams. It constructs a high-definition two-dimensional image for target detection by transmitting ultrasonic beams underwater and receiving the echo signals. It sets a new standard for excellence in underwater vision in black and turbid waters due to obtaining near-video quality dynamic images for the identification of objects underwater. In addition, split-beam echo-sounders have also been used on some occasions to monitor the movements of fishes. Despite the improvements achieved in fish monitoring techniques, the interpretation and classification of the data collected by the traditional acoustic techniques are often challenging and require extensive experience and effort. The DIDSON bridges the gap between existing fisheries-assessment sonar and optical systems. In a DIDSON, 96 transducer elements constitute a linear array and each element both transmits and receives acoustic beams such that echo amplitude is determined by the intensity of the reflected signal. It can obtain the distance and azimuth of the target from sonar images, but it is unable to acquire the elevation of the target from the images. To overcome this difficulty and obtain the fish distribution, a new method is proposed. Firstly, the sonar is fixed on the outside of the ship's rail and submerged in the water to collect fish's information through the investigation on navigation. At the same time, the beam emission direction is on the same plane with the sonar's moving direction.After data collection, image processing is conducted, including image construction, background elimination and target extraction from horizontal field-of-view. Target association based on Interacting Multiple Model Joint Probabilistic Data Association Filtering(IMMJPDAF) is carried out to deal with the extracted targets, thus the relations of one target in different frame images can be obtained. The 3 D target coordinates are acquired according to the spatial geometric relationship between the positions in two consecutive frame images. Finally, multiple target trajectories in 3 D space and the depth distribution of targets are obtained through the correlation algorithm. The experiment was carried out in Dishui Lake which is located in Shanghai. Experimental results showed that the proposed method can effectively acquire the fish movement tracks in 3 D space underwater and the distributions in depth. It also showed that most fish swam in the depth 3–5 meters. It will help to analyze the fish behavior and provide technical support for fishery resource assessment in a marine ranching.
In order to obtain the three-dimensional(3 D) distribution of fish in a marine ranching, a method using imaging sonar to calculate the 3 D coordinates of fish is proposed in this paper. The imaging sonar used in this research is a Dual-frequency Identification sonar(DIDSON). It is a multi-beam sonar that uses acoustic lens to form individual beams. It constructs a high-definition two-dimensional image for target detection by transmitting ultrasonic beams underwater and receiving the echo signals. It sets a new standard for excellence in underwater vision in black and turbid waters due to obtaining near-video quality dynamic images for the identification of objects underwater. In addition, split-beam echo-sounders have also been used on some occasions to monitor the movements of fishes. Despite the improvements achieved in fish monitoring techniques, the interpretation and classification of the data collected by the traditional acoustic techniques are often challenging and require extensive experience and effort. The DIDSON bridges the gap between existing fisheries-assessment sonar and optical systems. In a DIDSON, 96 transducer elements constitute a linear array and each element both transmits and receives acoustic beams such that echo amplitude is determined by the intensity of the reflected signal. It can obtain the distance and azimuth of the target from sonar images, but it is unable to acquire the elevation of the target from the images. To overcome this difficulty and obtain the fish distribution, a new method is proposed. Firstly, the sonar is fixed on the outside of the ship's rail and submerged in the water to collect fish's information through the investigation on navigation. At the same time, the beam emission direction is on the same plane with the sonar's moving direction.After data collection, image processing is conducted, including image construction, background elimination and target extraction from horizontal field-of-view. Target association based on Interacting Multiple Model Joint Probabilistic Data Association Filtering(IMMJPDAF) is carried out to deal with the extracted targets, thus the relations of one target in different frame images can be obtained. The 3 D target coordinates are acquired according to the spatial geometric relationship between the positions in two consecutive frame images. Finally, multiple target trajectories in 3 D space and the depth distribution of targets are obtained through the correlation algorithm. The experiment was carried out in Dishui Lake which is located in Shanghai. Experimental results showed that the proposed method can effectively acquire the fish movement tracks in 3 D space underwater and the distributions in depth. It also showed that most fish swam in the depth 3–5 meters. It will help to analyze the fish behavior and provide technical support for fishery resource assessment in a marine ranching.
引文
[1]Wild J J,Reid J M.Application of echo-ranging techniques to the determination of structure of biological tissues[J].Science,1952,115(2983):226-230.
[2]Cushing D H.Echo-surveys of fish[J].ICES Journal of Marine Science,1952,18(1):45-60.
[3]Bazigos G P.The design of fisheries statistical surveysinland waters[J].FAO Fisheries Technical Papers,1974,133:122.
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[6]Lee D J,Lee W W.Hydroacoustic investigations of demersal fisheries resources in the southeastern area of the Cheju Island,Korea-acoustical estimation of fish density and distribution[J].Journal of the Korean society of Fisheries Technology,1996,32(3):266-272.
[7]王靖,张超,王丹,等.清河水库鲢鳙鱼类资源声学评估--回波计数与回波积分法的比较[J].南方水产,2010,6(5):50-55.Wang J,Zhang C,Wang D,et al.Acoustic assessment of silver carp and bighead carp in Qinghe Reservoir:comparing echo-counting and echo-integrating methods[J].South China Fisheries Science,2010,6(5):50-55(in Chinese).
[8]Lee J B,Oh T Y,Yeon I J,et al.Estimation of demersal fish biomass using hydroacoustic and catch data in the marine ranching area(MRA)of Jeju[J].Journal of the Korean society of Fisheries Technology,2012,48(2):128-136.
[9]Wada M,Yasui S,Saville R,et al.The development of a remote fish finder system for set-net fishery[C]//2014Oceans-St.John's.St.John's,NL,Canada:IEEE,2014:1-6.
[10]Viscido S V,Parris J K,Grünbaum D.Individual behavior and emergent properties of fish schools:a comparison of observation and theory[J].Marine Ecology Progress Series,2004,273:239-249.
[11]冯春雷,李志国,黄洪亮,等.鱼类行为研究在捕捞中的应用[J].大连水产学院学报,2009,24(2):166-170.Feng C L,Li Z G,Huang H L,et al.Application of fish behavior research in fishing[J].Journal of Dalian Fisheries University,2009,24(2):166-170(in Chinese).
[12]徐盼麟,韩军,童剑锋.基于单摄像机视频的鱼类三维自动跟踪方法初探[J].水产学报,2012,36(4):623-628.Xu P L,Han J,Tong J F.Preliminary studies on an automated 3D fish tracking method based on a single video camera[J].Journal of Fisheries of China,2012,36(4):623-628(in Chinese).
[13]Jing D X,Han J,Wang X D,et al.A method to estimate the abundance of fish based on dual-frequency identification sonar(DIDSON)imaging[J].Fisheries Science,2017,83(5):685-697.
[14]Belcher E,Hanot W,Burch J.Dual-frequency identification sonar(DIDSON)[C]//Proceedings of 2002 International Symposium on Underwater Technology.Tokyo,Japan:IEEE,2002:187-192.
[15]Rakowitz G,Tu?er M,?íha M,et al.Use of high-frequency imaging sonar(DIDSON)to observe fish behaviour towards a surface trawl[J].Fisheries Research,2012,123-124:37-48.
[16]Grote A B,Bailey M M,Zydlewski J D,et al.Multibeam sonar(DIDSON)assessment of American shad(Alosa sapidissima)approaching a hydroelectric dam[J].Canadian Journal of Fisheries and Aquatic Sciences,2014,71(4):545-558.
[17]Price V E,Auster P J,Kracker L.Use of high-resolution DIDSON sonar to quantify attributes of predation at ecologically relevant space and time scales[J].Marine Technology Society Journal,2013,47(1):33-46.
[18]Jing D X,Han J,Wang G Y,et al.Dense multiple-target tracking based on dual frequency identification sonar(DIDSON)image[C]//Proceedings of the OCEANS2016-Shanghai.Shanghai,China:IEEE,2016:1-5.
[19]Belcher E,Matsuyama B,Trimble G.Object identification with acoustic lenses[C]//MTS/IEEE Conference and Exhibition OCEANS.Honolulu,HI,USA:IEEE,2001:6-11.
[20]Cho H,Gu J,Joe H,et al.Acoustic beam profile-based rapid underwater object detection for an imaging sonar[J].Journal of Marine Science and Technology,2015,20(1):180-197.
[21]郭睿利,郭云飞,张云龙,等.基于一种改进IMMJP-DA算法的地面目标跟踪[J].信息与电子工程,2012,10(4):406-411.Guo R L,Guo Y F,Zhang Y L,et al.Ground target tracking based on an improved IMMJPDA algorithm[J].Information and Electronic Engineering,2012,10(4):406-411(in Chinese).
[22]Chen B,Tugnait J K.Brief Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing[J].Automatica,2001,37(2):239-249.
[23]Blanchet J,Gallego G,Goyal V.A markov chain approximation to choice modeling[J].Operations Research,2016,64(4):886-905.
[2]Cushing D H.Echo-surveys of fish[J].ICES Journal of Marine Science,1952,18(1):45-60.
[3]Bazigos G P.The design of fisheries statistical surveysinland waters[J].FAO Fisheries Technical Papers,1974,133:122.
[4]Misund O A,Aglen A,Fr?naes E.Mapping the shape,size,and density of fish schools by echo integration and a high-resolution sonar[J].ICES Journal of Marine Science,1995,52(1):11-20.
[5]Bodholt H,Nes H,Solli H.A new echo-sounder system research[C]//ICES Council Meeting 1988.Copenhagen,Denmark:ICES,1983.
[6]Lee D J,Lee W W.Hydroacoustic investigations of demersal fisheries resources in the southeastern area of the Cheju Island,Korea-acoustical estimation of fish density and distribution[J].Journal of the Korean society of Fisheries Technology,1996,32(3):266-272.
[7]王靖,张超,王丹,等.清河水库鲢鳙鱼类资源声学评估--回波计数与回波积分法的比较[J].南方水产,2010,6(5):50-55.Wang J,Zhang C,Wang D,et al.Acoustic assessment of silver carp and bighead carp in Qinghe Reservoir:comparing echo-counting and echo-integrating methods[J].South China Fisheries Science,2010,6(5):50-55(in Chinese).
[8]Lee J B,Oh T Y,Yeon I J,et al.Estimation of demersal fish biomass using hydroacoustic and catch data in the marine ranching area(MRA)of Jeju[J].Journal of the Korean society of Fisheries Technology,2012,48(2):128-136.
[9]Wada M,Yasui S,Saville R,et al.The development of a remote fish finder system for set-net fishery[C]//2014Oceans-St.John's.St.John's,NL,Canada:IEEE,2014:1-6.
[10]Viscido S V,Parris J K,Grünbaum D.Individual behavior and emergent properties of fish schools:a comparison of observation and theory[J].Marine Ecology Progress Series,2004,273:239-249.
[11]冯春雷,李志国,黄洪亮,等.鱼类行为研究在捕捞中的应用[J].大连水产学院学报,2009,24(2):166-170.Feng C L,Li Z G,Huang H L,et al.Application of fish behavior research in fishing[J].Journal of Dalian Fisheries University,2009,24(2):166-170(in Chinese).
[12]徐盼麟,韩军,童剑锋.基于单摄像机视频的鱼类三维自动跟踪方法初探[J].水产学报,2012,36(4):623-628.Xu P L,Han J,Tong J F.Preliminary studies on an automated 3D fish tracking method based on a single video camera[J].Journal of Fisheries of China,2012,36(4):623-628(in Chinese).
[13]Jing D X,Han J,Wang X D,et al.A method to estimate the abundance of fish based on dual-frequency identification sonar(DIDSON)imaging[J].Fisheries Science,2017,83(5):685-697.
[14]Belcher E,Hanot W,Burch J.Dual-frequency identification sonar(DIDSON)[C]//Proceedings of 2002 International Symposium on Underwater Technology.Tokyo,Japan:IEEE,2002:187-192.
[15]Rakowitz G,Tu?er M,?íha M,et al.Use of high-frequency imaging sonar(DIDSON)to observe fish behaviour towards a surface trawl[J].Fisheries Research,2012,123-124:37-48.
[16]Grote A B,Bailey M M,Zydlewski J D,et al.Multibeam sonar(DIDSON)assessment of American shad(Alosa sapidissima)approaching a hydroelectric dam[J].Canadian Journal of Fisheries and Aquatic Sciences,2014,71(4):545-558.
[17]Price V E,Auster P J,Kracker L.Use of high-resolution DIDSON sonar to quantify attributes of predation at ecologically relevant space and time scales[J].Marine Technology Society Journal,2013,47(1):33-46.
[18]Jing D X,Han J,Wang G Y,et al.Dense multiple-target tracking based on dual frequency identification sonar(DIDSON)image[C]//Proceedings of the OCEANS2016-Shanghai.Shanghai,China:IEEE,2016:1-5.
[19]Belcher E,Matsuyama B,Trimble G.Object identification with acoustic lenses[C]//MTS/IEEE Conference and Exhibition OCEANS.Honolulu,HI,USA:IEEE,2001:6-11.
[20]Cho H,Gu J,Joe H,et al.Acoustic beam profile-based rapid underwater object detection for an imaging sonar[J].Journal of Marine Science and Technology,2015,20(1):180-197.
[21]郭睿利,郭云飞,张云龙,等.基于一种改进IMMJP-DA算法的地面目标跟踪[J].信息与电子工程,2012,10(4):406-411.Guo R L,Guo Y F,Zhang Y L,et al.Ground target tracking based on an improved IMMJPDA algorithm[J].Information and Electronic Engineering,2012,10(4):406-411(in Chinese).
[22]Chen B,Tugnait J K.Brief Tracking of multiple maneuvering targets in clutter using IMM/JPDA filtering and fixed-lag smoothing[J].Automatica,2001,37(2):239-249.
[23]Blanchet J,Gallego G,Goyal V.A markov chain approximation to choice modeling[J].Operations Research,2016,64(4):886-905.