High-resolution range image target recognition method based on complex densely connected neural network

Abstract

The invention discloses a high-resolution range image target recognition method based on a complex densely connected neural network, which includes: obtaining a radar range image data set; performing short-time Fourier transform on the radar range image data set to obtain a complex time spectrum data set; Divide the complex time spectrum data set into a complex time spectrum training data set and a complex time spectrum verification data set; construct a complex time spectrum densely connected neural network; use the complex time spectrum training data set to train a complex time spectrum densely connected neural network, and use the complex time spectrum verification data Set verify the trained complex densely connected neural network to obtain the trained complex densely connected neural network; use the trained complex densely connected neural network to identify the radar range image test data set to obtain the target recognition result. The present invention uses the constructed complex densely connected neural network to train and identify complex high-resolution range images, making full use of the characteristic structure in the signal, thereby improving the accuracy of the recognition network.

Description

Technical field [0001] The invention belongs to the field of radar technology, and specifically relates to a high-resolution range image target recognition method based on a complex densely connected neural network. Background technique [0002] Radar target recognition is to use the radar echo signal of the target to determine the target type. Broadband radar usually works in the optical zone, when the target can be regarded as consisting of a large number of scattering points with different intensities. High Resolution Range Profile (HRRP) is the vector sum of echoes from various scattering points on the target obtained using broadband radar signals. It reflects the distribution of scattering points on the target along the radar line of sight, contains important structural features of the target, and is widely used in the field of radar target recognition. [0003] Extracting recognition features from high-resolution range images is an important link in the radar target ...

AI Technical Summary

Problems solved by technology

[0004] However, due to the limitations of the basic network structure of the convolutional neural network and the residual neural network, when the recognition features are more complicated and the number of network layers increases, the problem of network degradation is prone to occur, which limits the performance of target recognition.

Images