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Adaptive Mainlobe Interference Suppression in Sparse Distributed Array Radar Based on Synthetic Wideband Signal

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Machine Learning and Intelligent Communications (MLICOM 2017)

Abstract

This paper proposes a mainlobe interference suppression method in distributed array radar (DAR) based on stepped frequency synthetic wideband signal. Due to the equivalent large aperture of DAR, it is possible to cancel the mainlobe interference without target signal suppression. The applying of stepped frequency synthetic wideband signal can avoid the different time delays arriving at each array compared with the traditional instantaneous wideband Chirp (linear frequency modulation) signal. Moreover, it can reduce the computational complexity. This method employs the narrowband adaptive processing to each sub-pulse of the stepped frequency signal, and then synthesizes the high resolution range profile (HRRP). As a result, mainlobe interference suppression under wideband signal is accomplished. Mainlobe interference suppression experiment is carried out by using an S-band experimental radar system, an S-band noise jammer and a target simulator. The measured data is processed employing the proposed method, and the result verifies the effectiveness of this algorithm.

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Acknowledgment

This work was supported by the Chang Jiang Scholars Programme under Grants T2012122, 111 Project of China under Grants B14010. The authors would like to thank Prof. Teng Long, Beijing Institute of Technology, China, for helpful comments and suggestions.

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Correspondence to Yuanyuan Song .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Luo, J., Zhang, H., Song, Y. (2018). Adaptive Mainlobe Interference Suppression in Sparse Distributed Array Radar Based on Synthetic Wideband Signal. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_22

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  • DOI: https://doi.org/10.1007/978-3-319-73447-7_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

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