Detection and tracking of land vehicle activity by offshore underwater acoustic arrays

1997 ◽  
Vol 102 (5) ◽  
pp. 3193-3193
Author(s):  
Gerald L. D’Spain ◽  
Lewis P. Berger ◽  
William S. Hodgkiss ◽  
William A. Kuperman ◽  
LeRoy M. Dorman ◽  
...  
Keyword(s):  
Underwater Acoustic ◽  
Land Vehicle ◽  
Detection And Tracking ◽  
Acoustic Arrays ◽  
Vehicle Activity

Offshore geoacoustic inversions using sounds from land vehicle activity

1998 ◽  
Vol 103 (5) ◽  
pp. 2936-2936
Author(s):  
Gerald L. D’Spain ◽  
William A. Kuperman ◽  
LeRoy M. Dorman ◽  
Lewis P. Berger ◽  
William S. Hodgkiss
Keyword(s):  
Land Vehicle ◽  
Vehicle Activity

scholarly journals Joint Passive Detection and Tracking of Underwater Acoustic Target by Beamforming-Based Bernoulli Filter with Multiple Arrays

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4022 ◽  
Author(s):  
Zhongyue Chen ◽  
Wen Xu
Keyword(s):  
Hybrid Method ◽  
Pearson Correlation ◽  
Tracking Accuracy ◽  
Underwater Acoustic ◽  
Passive Detection ◽  
Detection And Tracking ◽  
Target Track ◽  
Distributed Arrays ◽  
Acoustic Target ◽  
Bernoulli Filter

In this paper, improved Bernoulli filtering methods are developed to deal with the problem of joint passive detection and tracking of an underwater acoustic target with multiple arrays. Three different likelihood calculation methods based on local beamforming results are proposed for the Bernoulli filter updating. Firstly, multiple peaks, including both mainlobe and sidelobe peaks, are selected to form the direction-of-arrival (DOA) measurement set, and then the Bernoulli filter is used to extract the target track. Secondly, to make full use of the informations in the beamforming output, not only the DOAs but also their intensities, the beam powers are used as the input measurement sets of the filter, and an approach based on Pearson correlation coefficient (PCC) is developed for distinguishing between signal and noise. Lastly, a hybrid method of the former two is proposed in the case of fewer then three arrays. The tracking performances of the three methods are compared in simulations and experiment. The simulations with three distributed arrays show that, compared with the DOA-based method, the beam-based method and the hybrid method can both improve the target tracking accuracy. The processing results of the shallow water experimental data collected by two arrays show that the hybrid method can achieve a better tracking performance.

scholarly journals A Sensing and Tracking Algorithm for Multiple Frequency Line Components in Underwater Acoustic Signals

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4866 ◽  
Author(s):  
Xinwei Luo ◽  
Zihan Shen
Keyword(s):  
Signal To Noise Ratio ◽  
Acoustic Signals ◽  
Multiple Time ◽  
Time Varying ◽  
Multiple Frequency ◽  
Underwater Acoustic ◽  
Model Method ◽  
Detection And Tracking ◽  
Time Varying Frequency ◽  
Line Tracking

Reliable and efficient sensing and tracking of multiple weak or time-varying frequency line components in underwater acoustic signals is the topic of this paper. We propose a method for automatic detection and tracking of multiple frequency lines in lofargram based on hidden Markov model (HMM). Instead of being directly subjected to frequency line tracking, the whole lofargram is first segmented into several sub-lofargrams. Then, the sub-lofargrams suspected to contain frequency lines are screened. In these sub-lofargrams, the HMM-based method is used for detection of multiple frequency lines. Using image stitching and statistical model method, the frequency lines with overlapping parts detected by different sub-lofargrams are merged to obtain the final detection results. The method can effectively detect multiple time-varying frequency lines of underwater acoustic signals while ensuring the performance under the condition of low signal-to-noise ratio (SNR). It can be concluded that the proposed algorithm can provide better multiple frequency lines sensing ability while greatly reducing the amount of calculations and providing potential techniques for feature sensing and tracking processing of unattended equipment such as sonar buoys and submerged buoys.

Method for measuring the characteristics of underwater acoustic arrays in real environments

1994 ◽  
Vol 37 (1) ◽  
pp. 70-75
Author(s):  
S. V. Burenkov ◽  
N. I. Knyazeva ◽  
S. S. Naumov ◽  
E. A. Zenyutich
Keyword(s):  
Underwater Acoustic ◽  
Acoustic Arrays
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