The invention discloses a method for identifying a target in water.
Wavelet packet
decomposition threshold denoising is combined with component difference optimization to finish preprocessing of the
radiation noise signal; the problem that ocean
background noise affects
radiation noise time-frequency
feature extraction and interference classification and identification is solved; mapping from a one-dimensional
sequence signal to a two-dimensional space is achieved by adopting a
wavelet transformation method; the problem that a single
time domain or
frequency domain characteristic representation
signal is not comprehensive is avoided; two-dimensional
variational mode decomposition is carried out on the time-frequency characteristics; the
interference problem of a two-dimensional space noisesignal is solved; feature optimization is carried out on the obtained intrinsic mode component and a
signal is constructed according to the feature optimization, characteristic enhancement of time-frequency characteristics is achieved, two-dimensional variation
modal decomposition is carried out through employing an edge
mirror image method, a signal oscillation problem caused by an edge effect is avoided,
gradient descent training is carried out on a
small sample data set to update parameters of a classification
discriminator of the deep neural network, and the characteristic extraction model is made to have excellent generalization capability.