Signal Recognition of Polyphase-Coded Radar Signals Based on Multifeature Fusion

Xiaofeng Wang,Huixu Dong,Ruilan Tian,Gulam Nabi Alsath

doi:10.1155/2022/5848742

Abstract

For improving recognition accuracy of polyphase-coded radar signals under low signal to noise ratio (SNR), a recognition method based on multifeature and feature selection was proposed. First, feature parameters of polyphase-coded radar signals in time domain, frequency domain, and pseudo-Zernike moments of Choi-Williams distribution (CWD) were extracted, respectively. And then, redundancy features and small-correlation features were removed based on mutual information with greedy idea. Finally, recognition of polyphase-coded radar signals was implemented using support vector machines (SVM). The experimental results showed that the average recognition accuracy of proposed method was over 90% when SNR is 0 dB, and the recognition performance was superior to the existing methods.

Highlights

Low probability of intercept (LPI) has become a necessary technology for modern radar [1,2,3]
Polyphase-coded radar signals adopts phase encoding to approximate chirp or step chirp for obtaining the advantages of frequency modulation and phase modulation at the same time. It is precisely because the polyphase-coded radar signals has both the characteristics of frequency modulation and phase modulation, and it is difficult to intercept and recognize it, which is a key problem that needs to be solved in electronic intelligence system (ELINT) [5]
Ere are five coded types of polyphase-coded radar signals. erefore, five-class support vector machines (SVM) is shown in Figure 3. e classifier has a total of 10 two-class SVM. e input feature parameters first pass through the top-level SVM and continuously pass into the lower-level SVM. e final recognition result is output by the underlying SVM

Summary

Introduction

Low probability of intercept (LPI) has become a necessary technology for modern radar [1,2,3]. Polyphase-coded radar signals adopts phase encoding to approximate chirp or step chirp for obtaining the advantages of frequency modulation and phase modulation at the same time It is precisely because the polyphase-coded radar signals has both the characteristics of frequency modulation and phase modulation, and it is difficult to intercept and recognize it, which is a key problem that needs to be solved in electronic intelligence system (ELINT) [5]. Lunden and Koivunen [10] constructed a feature vector based on the instantaneous frequency characteristics of the signal and the time– frequency distribution image characteristics to realize polyphase-coded radar signals recognition. Recognition performance of this method depends on the frequency estimation.

Multidomain Feature Extraction

Feature Selection Based on Mutual Information

Experiment and Analysis

Findings

Conclusions