Motion tracking of fish and bubble clouds in synthetic aperture sonar data

被引:1
|
作者
Marston, Timothy M. [1 ]
Hall, Bernard R. [2 ,5 ]
Bassett, Christopher [1 ]
Plotnick, Daniel S. [3 ]
Kidwell, Autumn N. [4 ]
机构
[1] Univ Washington, APL, Seattle, WA 98103 USA
[2] Washington State Univ, Pullman, WA 99163 USA
[3] Penn State Univ, ARL, State Coll, PA 16801 USA
[4] Univ Texas Austin, ARL, Austin, TX 78758 USA
[5] Univ Idaho, Moscow, ID 83844 USA
来源
关键词
BUOYANT PLUME; WATER; DENSITY; FRONTS;
D O I
10.1121/10.0025384
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Data captured by a Synthetic Aperture Sonar (SAS) near Mobile Bay during the 2021 Undersea Remote Sensing experiment funded by the Office of Naval Research reveals near surface bubble clouds from wave breaking events and a large aggregation of fish. Tools developed for using SAS data to image hydrodynamic features in the water column were applied to observations of the bubble clouds and fish aggregation. Combining imagery and height data captured by the sonar array with a detection and tracking algorithm enables the trajectories, velocities, and behavior of fish in the aggregation to be observed. Fitting the velocity and height data of the tracked objects to a Gaussian mixture model and performing cluster analysis enables an estimate of the near-surface ambient velocity via observation of the movement of the bubble traces and the general direction of motion of the fish aggregation. We find that the velocity traces associated with bubbles are consistent with ambient currents as opposed to the direction of propagating wave crests while velocities of fish indicate relatively large, pelagic species.
引用
收藏
页码:2181 / 2191
页数:11
相关论文
共 50 条
  • [1] Motion compensation on synthetic aperture sonar images
    Heremans, R.
    Acheroy, M.
    Dupont, Y.
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XII, 2006, 6365
  • [2] Motion compensation on synthetic aperture sonar images
    Heremans, Roel
    Acheroy, Marc
    Dupont, Yves
    2006 IEEE ULTRASONICS SYMPOSIUM, VOLS 1-5, PROCEEDINGS, 2006, : 152 - +
  • [3] Motion Compensation Algorithm of Synthetic Aperture Sonar Based on Multisensor Data Fusion
    Zhang Y.
    Li G.-X.
    Zhang P.-F.
    Wei L.-Z.
    Liu J.-Y.
    Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications, 2017, 40 (05): : 82 - 86
  • [4] Unsupervised learning of platform motion in synthetic aperture sonar
    Xenaki, Angeliki
    Gips, Bart
    Pailhas, Yan
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2022, 151 (02): : 1104 - 1114
  • [5] Motion compensation of synthetic aperture sonar with acceleration sensors
    Sawa, Takao
    Kamakura, Tomoo
    Aoki, Taro
    Tahara, Jyunichiro
    JAPANESE JOURNAL OF APPLIED PHYSICS PART 1-REGULAR PAPERS BRIEF COMMUNICATIONS & REVIEW PAPERS, 2007, 46 (7B): : 4977 - 4981
  • [6] SYNTHETIC APERTURE SONAR
    SATO, T
    UEDA, M
    FUKUDA, S
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 1973, 54 (03): : 799 - 802
  • [7] SYNTHETIC APERTURE SONAR
    GIDA, AS
    GRIFFITHS, JWR
    ULTRASONICS, 1987, 25 (06) : 349 - 350
  • [8] Multilateration motion compensation for circular synthetic aperture sonar imaging
    Zeng, Sai
    Fan, Wei
    Du, Xuanmin
    Zhou, Shengzeng
    Shengxue Xuebao/Acta Acustica, 2021, 46 (06): : 1070 - 1080
  • [9] Motion compensation of AUV-based synthetic aperture sonar
    Cook, DA
    Christoff, JT
    Fernandez, JE
    OCEANS 2003 MTS/IEEE: CELEBRATING THE PAST...TEAMING TOWARD THE FUTURE, 2003, : 2143 - 2148
  • [10] Synthetic Aperture Sonar Motion Compensation using Deep Learning
    Emigh, Matthew
    Prater, James
    13TH EUROPEAN CONFERENCE ON SYNTHETIC APERTURE RADAR, EUSAR 2021, 2021, : 255 - 258