Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10005645,
  title    = {Ship Detection Requirements Analysis for Different Sea States: Validation on Real SAR Data},
  author    = {Jaime Martín-de-Nicolás and  David Mata-Moya and  Nerea del-Rey-Maestre and  Pedro Gómez-del-Hoyo and  María-Pilar Jarabo-Amores},
  country   = {Spain},
  institution={University of Alcala},
  abstract  = {Ship detection is nowadays quite an important issue
in tasks related to sea traffic control, fishery management and ship
search and rescue. Although it has traditionally been carried out
by patrol ships or aircrafts, coverage and weather conditions and
sea state can become a problem. Synthetic aperture radars can
surpass these coverage limitations and work under any climatological
condition. A fast CFAR ship detector based on a robust statistical
modeling of sea clutter with respect to sea states in SAR images
is used. In this paper, the minimum SNR required to obtain a
given detection probability with a given false alarm rate for any
sea state is determined. A Gaussian target model using real SAR
data is considered. Results show that SNR does not depend heavily
on the class considered. Provided there is some variation in the
backscattering of targets in SAR imagery, the detection probability
is limited and a post-processing stage based on morphology would
be suitable.},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {10},
  number    = {11},
  year      = {2016},
  pages     = {1373 - 1378},
  ee        = {http://waset.org/publications/10005645},
  url       = {http://waset.org/Publications?p=119},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 119, 2016},
}