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  • Jia, WenkaiUniversity of Electronic Science and Technology of China (author)

Waveform optimization with SINR criteria for FDA radar in the presence of signal-dependent mainlobe interference

  • Article/chapterEnglish2023

Publisher, publication year, extent ...

  • Elsevier BV,2023

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  • LIBRIS-ID:oai:lup.lub.lu.se:c8de36a4-5758-46d4-8788-12ef51f732b7
  • https://lup.lub.lu.se/record/c8de36a4-5758-46d4-8788-12ef51f732b7URI
  • https://doi.org/10.1016/j.sigpro.2022.108851DOI

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  • Language:English
  • Summary in:English

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  • Subject category:art swepub-publicationtype
  • Subject category:ref swepub-contenttype

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  • In this paper, we focus on the design of the transmit waveforms of a frequency diverse array (FDA) in order to improve the output signal-to-interference-plus-noise ratio (SINR) in the presence of signal-dependent mainlobe interference. Since the classical multi-carrier matched filtering-based FDA receiver cannot effectively utilize the waveform diversity of FDA, a novel FDA receiver framework based on multi-channel mixing and low pass filtering is developed to keep the separation of the transmit waveform at the receiver side, while preserving the FDA range-controllable degrees of freedom. Furthermore, a range-angle minimum variance distortionless response beamforming technique is introduced to synthesize receiver filter weights with the ability to suppress a possible signal-dependent mainlobe interference. The resulting FDA transmit waveform design problem is initially formulated as an optimization problem consisting of a non-convex objective function and multiple non-convex constraints. To efficiently solve this, we introduce two algorithms, one based on a signal relaxation technique, and the other based on the majorization minimization technique. The preferable performance of the proposed multi-channel low pass filtering receiver and the optimized transmit waveforms is illustrated using numerical simulations, indicating that the resulting FDA system is not only able to effectively suppress mainlobe interference, but also to yield estimates with a higher SINR than the FDA system without waveform optimization.

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  • Jakobsson, AndreasLund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,LTH profilområde: AI och digitalisering,LTH profilområden,LU profilområde: Naturlig och artificiell kognition,Lunds universitets profilområden,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,LTH Profile Area: AI and Digitalization,LTH Profile areas,Faculty of Engineering, LTH,LU Profile Area: Natural and Artificial Cognition,Lund University Profile areas(Swepub:lu)mats-aaj (author)
  • Wang, Wen QinUniversity of Electronic Science and Technology of China (author)
  • University of Electronic Science and Technology of ChinaMatematisk statistik (creator_code:org_t)

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  • In:Signal Processing: Elsevier BV2040165-1684

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