Fractional Fourier Transform and Compressed Sensing Adaptive Countering Smeared Spectrum Jamming

Yang ZHAO; Chaoxuan SHANG; Zhuangzhi HAN; Ning HAN; Hui XIE

doi:10.11999/JEIT180569

Volume 41 Issue 5

Apr. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(5): 1047-1054

Yang ZHAO, Chaoxuan SHANG, Zhuangzhi HAN, Ning HAN, Hui XIE. Fractional Fourier Transform and Compressed Sensing Adaptive Countering Smeared Spectrum Jamming[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1047-1054. doi: 10.11999/JEIT180569

Citation:

Yang ZHAO, Chaoxuan SHANG, Zhuangzhi HAN, Ning HAN, Hui XIE. Fractional Fourier Transform and Compressed Sensing Adaptive Countering Smeared Spectrum Jamming[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1047-1054. doi: 10.11999/JEIT180569

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Fractional Fourier Transform and Compressed Sensing Adaptive Countering Smeared Spectrum Jamming

doi: 10.11999/JEIT180569

1.
Army Engineering University, Shijiazhuang 050003, China
2.
32181 of PLA, Xi’an 710032, China

Funds: The National Natural Science Foundation of China (61601496)

Received Date: 2018-06-11
Rev Recd Date: 2018-12-12

Available Online: 2018-12-28

Publish Date: 2019-05-01

Abstract

Abstract

SMeared SPectrum (SMSP) jamming has lots of coupling in time and frequency domain with Linear Frequency Modulated (LFM) radar signals, which has good jamming performance. This paper proposes a signal processing method for countering SMSP jamming in information domain. According to the formulation and characteristics of SMSP signal, the jamming dictionary is changed automatically, the frequency modulation rate of LFM and SMSP signal is matcheal at the same time, the compressed sampling model is consructed and reconstruction of signal is carried out based on convex optimization. Finally, the recognition of jamming signal and extraction of radar signal are achieved. Pei type fractional Fourier decomposition method is used in construction of redundant dictionary. Modulation and demodulation between time and frequency domain are avoided in this method, which leads to improvement in fewer iteration times and higher arithmetic speed.
- Signal processing,
- SMeared SPectrum (SMSP),
- Fractional Fourier Transform (FrFT),
- Compressed sensing,
- Morphological theory

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References(22)

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