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.
This work was supported by the Scientific and Technological Development Foundation of Southwest Jiaotong University (2006A09) and by the National Natural Science Foundation of China (60572143).
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Zhang, G., Rong, H. (2007). Improved Quantum-Inspired Genetic Algorithm Based Time-Frequency Analysis of Radar Emitter Signals. In: Yao, J., Lingras, P., Wu, WZ., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds) Rough Sets and Knowledge Technology. RSKT 2007. Lecture Notes in Computer Science(), vol 4481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72458-2_60
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DOI: https://doi.org/10.1007/978-3-540-72458-2_60
Publisher Name: Springer, Berlin, Heidelberg
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