The invention relates to a marine target
feature detection method applying dynamic
time sequence weight, and belongs to the technical field of
radar detection algorithms. In order to overcome the defect that
time sequence information is not fully utilized during AR
model fitting in the prior art, the method comprises the following steps: step 1, carrying out
feature extraction on
original data to obtain observed values of features; 2, predicting the features obtained in the step 1 to obtain predicted values of the features; step 3, carrying out dynamic weighted fusion on the observation value in the step 1 and the predicted value in the step 2 to obtain a
time sequence fusion value of the features; and 4, detecting the time sequence fusion value obtained in the step 3 by adopting a convex
hull detector to obtain a detection probability. According to the method, the feature time sequence predicted value and the feature observed value are fused through dynamic calculation, the feature time sequence is fully utilized, the fusion feature variance is reduced, the time
sequence feature separability is enhanced, and the target detection probability is improved.