Radar Emitter Signal Detection with Convolutional Neural Network

Liu，Zhenrong1; Shi，Yankun1; Zeng，Yuan2; Gong，Yi3

10.1109/ICAIT.2019.8935926

2019-10-01

978-1-7281-4779-6

2019 IEEE 11th International Conference on Advanced Infocomm Technology, ICAIT 2019

48-51

18-20 Oct. 2019

Jinan, China

Institute of Electrical and Electronics Engineers Inc.

In this paper, we propose a deep convolutional neural network (CNN) based automatic detection algorithm for recognizing radar emitter signals. The algorithm leverages on the structure estimation power of deep CNN and the capability of time-frequency image processing for radio signal representation. We transform raw radio signals into time-frequency image using the Choi-Williams distribution function. We compare the proposed method with Belief Propagation (BP) and Support Vector Machine (SVM) based methods in terms of recognition accuracy versus signal-to-noise-ratio. The experiments demonstrate that the proposed CNN network with time-frequency image processing achieves very competitive results on the testing datasets.

convolutional neural network Radar emitter signal detection signal representation time-frequency image processing

第一

英语

EI

20200408063168

Backpropagation ; Convolution ; Deep neural networks ; Distribution functions ; Frequency estimation ; Image processing ; Neural networks ; Radar imaging ; Radar transmitters ; Signal to noise ratio ; Support vector machines ; Tracking radar

Information Theory and Signal Processing:716.1 ; Radar Systems and Equipment:716.2 ; Computer Software, Data Handling and Applications:723 ; Artificial Intelligence:723.4 ; Probability Theory:922.1

2-s2.0-85078575699

Scopus

1.Southern University of Science and Technology,Department of Electrical and Electronic Engineering,Shenzhen,11849160,China
2.Southern University of Science and Technology,Academy for Advanced Interdisciplinary Studies,Shenzhen,China
3.Southern University of Science and Technology,Shenzhen Engineering Laboratory of Intelligent Information Processing for IoT,Shenzhen,China

Liu，Zhenrong,Shi，Yankun,Zeng，Yuan,et al. Radar Emitter Signal Detection with Convolutional Neural Network[C]:Institute of Electrical and Electronics Engineers Inc.,2019:48-51.