Ship detection using Neyman-Pearson criterion in marine environment

This paper presents Neyman Pearson (N-P) criterion based detector for ship detection in marine environment. Statistical modeling of ambient noise data with and without ship noise, collected in the shallow waters of the Bay of Bengal, are utilized to build the detector. The noise data with and without ship noise are collected using the hydrophones at the depths of 5 m/15 m and 3 m/5 m, respectively, from the ocean surface. The ambient noise without and with ship noise is shown to have generalized extreme value and generalized Gaussian distribution, respectively. The presence of a ship leads to changes in the statistics of the ambient noise. This statistical characterization is used for designing a N-P criterion based log likelihood ratio test for the detection of presence of a ship. The proposed method detects the presence of a ship with an accuracy of 98.33%.