Receiver depth selection for passive sonar systems

1991 ◽  
Vol 16 (3) ◽  
pp. 267-278 ◽  
Author(s):  
C. Ferla ◽  
M.B. Porter
Keyword(s):  
Passive Sonar ◽  
Sonar Systems ◽  
Selection For

Sonar operator performance considerations in passive sonar systems

1975 ◽  
Author(s):  
R. J. Hornick ◽  
G. Yamashita ◽  
J. E. Robinson ◽  
H. J. Winkler
Keyword(s):  
Operator Performance ◽  
Passive Sonar ◽  
Sonar Systems ◽  
Performance Considerations

SYNTHESIS OF NEURAL NETWORK ALGORITHMS FOR CLASSIFICATION OF MARINE OBJECTS IN LOW-FREQUENCY PASSIVE SONAR SYSTEMS

2019 ◽  
pp. 3-8
Author(s):  
O.A. Andreev ◽  
A.T. Trofimov
Keyword(s):  
Neural Network ◽  
Probabilistic Models ◽  
Low Frequency ◽  
Gaussian Mixture ◽  
Classification Systems ◽  
Classification Algorithms ◽  
Correct Classification ◽  
Passive Sonar ◽  
Sonar Systems

The paper addresses the issue of insuring the required probability of correct classification of marine objects in low-frequency passive sonar systems. The solution to the issue is sought through the application of methods for the synthesis of neural network classification algorithms using poly-Gaussian probabilistic models (Gaussian mixture models, GMM). It is shown that the use of GMM makes it possible to solve a number of problems specific to the issue; classification algorithms synthesized using mentioned methods can be implemented in the form of neural networks, which in turn can be described in C++/VHDL to create endpoint computing devices or software systems. The results of modeling of synthesized classification algorithms on experimental data are presented; it is demonstrated that such algorithms make it possible to increase the probability of correct classification of marine objects and to satisfy typical requirements for classification systems in low-frequency passive sonar systems.

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