HRRP-based target recognition with deep contractive neural network

Abstract

One of the radar high resolution range profile (HRRP) target recognition issues is the existence of noise interference, especially for the ground target. The recognition performance of traditional shallow methods degrades as suffering from the limited capability of extracting robust and discriminative features. In this paper, a novel deep neural network called stacked denoising and contractive auto-encoder (SDCAE) is designed for millimeter wave radar HRRP recognition. To enhance the capability of learning robust structure and correlations from corrupted HRRP data, a denoising contractive auto-encoder is designed by combining the advantages of denoising auto-encoder and contractive auto-encoder. As an extension of deep auto-encoders, SDCAE inherits the advantage of enhancing the robustness of features via reducing external noise, retaining local invariance to obtain more discriminative representations of training samples. Experimental results demonstrate the superior performance of the proposed method over traditional methods, especially in noise interference condition and with few training samples.

Keywords:

• High resolution range profile
• target recognition
• deep neural network
• auto-encoder

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Yilu Ma

Yilu Ma received the BS degree in the School of Electronic and Optical Engineering from Nanjing University of Science and Technology, Nanjing, China, in 2014. Then he was elected into the successive master and doctor program. He is currently working toward the PhD degree with the Electronic and Optical Engineering, Nanjing University of Science and Technology. His research interests are in the fields of radar automatic target recognition (RATR), and signal processing.

Li Zhu

Li Zhu received the MS and PhD degrees in Electrical Engineering from Nanjing University of Science and Technology in 2004 and 2011, respectively. Currently, she is an assistant professor in Nanjing University of Science and Technology in China, who studies on millimeter wave target detecting.

Yuehua Li

Yuehua Li received the MS and PhD degrees, both in electronic engineering, from Nanjing University of Science and Technology, Nanjing, China, in 1989 and 1999, respectively. Currently, he is a Professor at Nanjing University of Science and Technology. He is the dean of the Detection and Control Engineering Department. His research work focuses on the areas of radar signal processing, weak signal detection and the design of high-speed signal processing system.