Waveform Design for the Radar-Communications Coexistence With Good Correlation Properties
编号:125 访问权限:仅限参会人 更新:2020-08-05 10:17:28 浏览:396次 口头报告

报告开始:2020年06月08日 14:20(Asia/Shanghai)

报告时间:20min

所在会场:[S] Special Session [SS06] Cognitive Waveform Diversity Design And Signal Processing

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摘要
We deal with the waveform design problem for the radar-communications coexistence (RCC) that ensures low correlations of the waveform and meanwhile implements efficient fast-time information embedding (IE). Two designs of unimodular waveforms are respectively proposed, wherein we evaluate the integrated sidelobe level (ISL) to find optimal waveform correlations for the radar transmission and exploit the attributes of waveform phases with large degrees of freedom to embed communication symbols. The first design is an offline strategy, which simply uses the phase initialization for waveform generation to embed communication symbols. It requires only a predefined database indexing between the waveform initialization and its emitted version, which enables the lowest ISL. While the second design employs the phase difference between any two waveform elements for IE, whose accuracy to approaching desirable phases is elaborately transformed into a quadratic form and jointly designed with the minimization of ISL. We formulate this design into a nonconvex optimization problem with a compound objective involving the outer product of the waveform vector. To solve this problem, we apply the majorization-minimization technique, based on which an efficient algorithm that iterates with a closed-form solution is devised. Simulation results verify the effectiveness of our designs developed for the RCC.
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报告人
Yongzhe Li
Beijing Institute of Technology & School of Information and Electronics, China

稿件作者
Yongzhe Li Beijing Institute of Technology & School of Information and Electronics, China
Ran Tao Beijing Institute of Technology, China
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重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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