Improved quantum-inspired genetic algorithm based time-frequency analysis of radar emitter signals

Authors:
Gexiang Zhang;Haina Rong
Affiliations:
School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China;School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

Citing 3
Cited 1

Quantum-Inspired Genetic Algorithm Based Time-Frequency Atom Decomposition

ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Intra-pulse modulation recognition of advanced radar emitter signals using intelligent recognition method

RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Size of the dictionary in matching pursuit algorithm

IEEE Transactions on Signal Processing

Quantum-inspired evolutionary algorithms: a survey and empirical study

Journal of Heuristics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper uses an improved quantum-inspired genetic algorithm (IQGA) based time-frequency atom decomposition to analyze the construction of radar emitter signals. With time-frequency atoms containing the detailed characteristics of a signal, this method is able to extract specific information from radar emitter signals. As IQGA has good global search capability and rapid convergence, this method can obtain time-frequency atoms of radar emitter signals in a short span of time. Binary phase shift-key radar emitter signal and linear-frequency modulated radar emitter signal are taken for examples to analyze the structure of decomposed time-frequency atoms and to discuss the difference between the two signals. Experimental results show the huge potential of extracting fingerprint features of radar emitter signals.