基于迭代凸优化的恒模波形合成方法

李秀友; 薛永华; 董云龙; 关键

doi:10.11999/JEIT141593

基于迭代凸优化的恒模波形合成方法

doi: 10.11999/JEIT141593

基金项目:

国家自然科学基金(61002045, 61179017, 61102167)和航空科学基金(20095184004)

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- 被引次数: 0
出版历程
- 收稿日期: 2014-11-07
- 修回日期: 2015-05-21
- 刊出日期: 2015-09-19

Constant Modulus Waveform Synthesis Based on Iterative Convex Optimization

摘要

摘要: 针对认知雷达合成的时域恒模波形能量谱误差大的问题，该文提出了一种基于迭代凸优化的恒模波形合成方法。该方法首先将波形合成过程转化成峰均功率比(PAPR)约束下的优化问题，克服了常规波形合成过程中时域和频域独立优化导致的整体收敛速度慢，局部最优值能量谱误差大的问题。其次通过最小化加权误差矢量值(WEVM)降低阻带功率水平，提高干扰及强杂波抑制能力。最后通过一系列变换操作将优化问题转化成二阶锥规划(SOCP)问题求解。计算机仿真验证了所提算法的有效性。
- 认知雷达 /
- 恒模波形 /
- 凸优化 /
- 峰均功率比
Abstract: In order to solve the problem of large energy spectral density error of the constant modulus waveform synthesized in cognitive radar. A new waveform design algorithm based on iterative convex optimization is proposed. Firstly, in order to solve the problems of slow convergence speed and large error of energy spectral density, this algorithm transforms the waveform synthesis process into an optimization problem constrained by Peak-to-Average Power Ratio (PAPR). Secondly, Weighting Error Vector Magnitude (WEVM) is minimized to reduce stop-band power and suppress the interference and the clutter. Finally, the optimization problem is transformed into Second-Order Cone Programming (SOCP) problem. Simulation results verify the effectiveness of the proposed algorithm.
- Cognitive radar /
- Constant modulus waveform /
- Convex optimization /
- Peak-to-Average Power Ratio (PAPR)

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