The application discloses a semi-supervised HRRP
noise label filtering method based on early learning guidance, comprising the following steps: constructing an HRRP training
data set and a deep neural
network model; pre-training the deep neural
network model; predicting the HRRP training
data set by using the pre-trained
network model and dividing the HRRP training
data set into two data sets according to the confidence; constructing a known
label data set and an unknown
label data set to form a semi-
supervised training data set and performing data enhancement; semi-
supervised training the network model by using the enhanced data; generating the label of the unknown label data set by using the semi-supervised trained network model and fully
supervised training the network model; and target recognition of the HRRP data by using the fully supervised trained network model. The application uses a generalized cross-entropy
loss function in the early learning training stage of the model, proposes a data enhancement scheme suitable for HRRP, can better reduce the influence of
noise labels on the model, and has better stability and implementability.