Reducing false alarms in automated target recognition using local sea-floor characteristics

@article{Daniell2014ReducingFA,
  title={Reducing false alarms in automated target recognition using local sea-floor characteristics},
  author={O. Daniell and Y. Petillot and S. Reed and J. V{\'a}zquez and A. Frau},
  journal={2014 Sensor Signal Processing for Defence (SSPD)},
  year={2014},
  pages={1-5}
}
  • O. Daniell, Y. Petillot, +2 authors A. Frau
  • Published 2014
  • Geography
  • 2014 Sensor Signal Processing for Defence (SSPD)
  • This paper describes the use of local sea-floor characteristics to train a neural network to remove false alarms from an Automatic Target Recognition (ATR) algorithm. We demonstrate that this reduces the Probability of False Alarm (PFA) in difficult areas without impacting the Probability of Detection (PD) in flat areas. The sea-floor characteristics are calculated from the texture and appearance of clutter on the seafloor. Textural characteristics are extracted using a Dual Tree Wavelet (DTW… CONTINUE READING

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