Classification of propeller vehicle using LOFAR cubic splines interpolation in combination with triple loss variational auto encoder



  • Bach Nhat Hoang Academy of Military Science and Technology
  • Nguyen Trung Kien (Corresponding Author) Academy of Military Science and Technology
  • Vu Le Ha Academy of Military Science and Technology



Underwater processing; Sonar; Interpolation; Triple loss.


In the field of ocean acoustics, both traditional and modern underwater signal processing methods have recently achieved positive results. For sonar problems serving national defense and security tasks, the need for timely and accurate classification of propeller ship types is of top importance. This study presents an underwater signal processing model for the purpose of detecting and classifying propeller ships with improved LOFAR techniques by cubic splines interpolation (CSI) combined with probability distribution in the hidden space domain. The results of the proposed model, tested on real data sets, show that the classification accuracy has increased by 10%, achieving an efficiency of 88% compared to the previous models. This solution also demonstrates that the model combining traditional and modern methods can effectively classify actual signals even when the amount of data is lacking and the signal-to-noise ratio is low.


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How to Cite

Bạch, N. H., T. K. Nguyễn, and L. H. Vũ. “Classification of Propeller Vehicle Using LOFAR Cubic Splines Interpolation in Combination With Triple Loss Variational Auto Encoder”. Journal of Military Science and Technology, no. 80, June 2022, pp. 39-48, doi:10.54939/1859-1043.j.mst.80.2022.39-48.



Research Articles