Open AccessExtraction and Sequential Recognition of MFR Pulse Groups in Intercepted Pulse Trains
Author(s) -
Shuo Yuan,
Tao Xu,
Min Zhang,
Zhangmeng Liu
Publication year - 2022
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2022.3211938
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
A pulse group is defined as a pulse sequence performing a certain task, such as searching or tracking, in a specific range and azimuth. It serves as a basic information unit of MFR pulse trains. In passive radar data processing, the pulse group structure provides vital support for many applications, such as sequential pulse deinterleaving, pulse group recognition, and working mode identification. In recent years, research related to pulse groups has attracted much attention. In this paper, we propose a pulse group extraction method based on semantic coding and temporal feature clustering. The method can automatically extract pulse group structures from intercepted pulse trains polluted by missing pulses and interferential ones. Furthermore, a temporal pattern recognition method based on the finite state automaton (FSA) is also proposed. Based on extracted pulse group structures, the FSA model achieves sequential recognition of pulse groups in newly intercepted pulse streams. The simulation section verifies the performance of the proposed methods in pulse group extraction and sequential recognition.