Radar target HRRP robust identification method in noise environment

Abstract

The invention belongs to the field of radar target identification, and discloses a radar target HRRP robust identification method in a noise environment. The radar target HRRP robust identification method comprises the steps of: acquiring a target high-resolution range profile (HRRP) by means of a radar, carrying out power normalization on the target high-resolution range profile, and dividing HRRP data into a training sample set and a test sample set; adding noise with different signal-to-noise ratios into part of training samples of each type of targets while the remaining training samples are unchanged, and then normalizing the whole training sample set of all target types; utilizing the obtained training samples to train a convolutional neural network which is provided by the inventionand combined with a residual block, an inception structure and a noise reduction self-encoding layer, so as to obtain a trained convolutional neural network; and testing test samples polluted by noise under different signal-to-noise ratio conditions to obtain an identification result. According to the radar target HRRP robust identification method, the interference of noise on identification canbe effectively reduced, a stable anti-noise identification model is obtained through deep learning, and robust radar target identification under the condition of a wide signal-to-noise ratio range canbe achieved.

Description

technical field [0001] The invention relates to the field of radar target recognition, and more specifically relates to a radar target HRRP robust recognition method in a noise environment. Background technique [0002] Traditional radar target recognition technology relies on artificially designed features, and the integrity and effectiveness of these features are often lacking strong guarantees, and the complex electromagnetic environment will interfere with the recognition results, leading to extreme challenges in the accuracy and robustness of traditional radar target recognition technology. big challenge. Deep learning technology can automatically extract the essential features of the target. This end-to-end learning method greatly improves the accuracy and robustness of target recognition. [0003] The application of deep learning to radar target recognition is generally divided into training phase and testing phase. At present, the training sample set is usually obt...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is: Aiming at the problem that the test sample is polluted by noise, resulting in a greatly reduced recognition rate, a radar target HRRP robust recognition method in a noisy environment is proposed to reduce the interference of noise on recognition to obtain a stable Noise Resistant Classification Model

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