摘要
为满足雷达复杂工作场景任务需求,提出一种基于主优化(MM)算法的低相关旁瓣、稀疏频谱波形设计方法;该方法首先建立最小化积分旁瓣电平准则下的恒模发射信号模型,并考虑工作频段拥塞情况下波形稀疏频谱特性,进而建立低相关旁瓣和稀疏频谱任务需求下的主优化(MM)目标函数表达式,最后利用主优化(MM)思想构造最小化积分旁瓣电平或稀疏频谱的算法框架。仿真结果表明,该算法能够有效降低积分旁瓣电平,并能够在干扰频段形成频带陷波,且在码长较长时仍具有较佳效果。
To tackle the sophisticated radar scene, a novel method based on majorization-minimization mechanism is presented to design waveforms with low correlation sidelobes and sparse spectrum. Firstly, the unimodular waveform, in the case of minimizing the integrated sidelobe level as well as suppressing the con- gested spectrum, is formulated. Next, the objective function incorporating the idea of majorization-minimiza- tion is derived, and then, the MISL algorithm and the weighted spectral-MISL algorithm are proposed. Sim- ulations demonstrate that these algorithms can obtain low integrated sidelobe level and sparse spectrum in the suppressed bands, which also performed for long waveforms.
作者
宋阳春
唐旭艳
冯翔
赵宜楠
SONG Yangchun TANG Xuyan FENG Xiang ZHAO Yinan(School of Information and Electrical Engineering, Harbin Institute of Technology at Weihai , Weihai 264209, China Shanghai Electro-Mechanical Engineering Institute, Shanghai 200233, China)
出处
《雷达科学与技术》
北大核心
2017年第2期159-165,共7页
Radar Science and Technology
基金
国家自然科学基金(No.61371181)
关键词
稀疏频谱
恒模波形
低相关旁瓣
主优化(MM)算法
sparse spectrum
unimodular waveform
low correlation sidelobe
majorization-minimiza- tion(MM) algorithm