一种用于NLFM波形设计的相位改进算法 自相关函数中的旁瓣电平

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摘要翻译：
本文提出了一种相位改进算法，用于设计升余弦、Taylor、Chebyshev和Kaiser四个窗口的非线性调频(NLFM)信号。我们已经用固定相位法设计了NLFM信号。对相位改进算法中自相关函数的峰值旁瓣电平的仿真结果表明，与固定相位法相比，自相关函数的峰值旁瓣电平平均降低了约5 dB。此外，为了评价相位改进算法的效率，计算了每次迭代的最小误差值。
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英文标题：
《Phase Improvement Algorithm for NLFM Waveform Design to Reduction of
  Sidelobe Level in Autocorrelation Function》
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作者：
Roohollah Ghavamirad, Mohammad Ali Sebt and Hossein Babashah
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  In this paper, a phase improvement algorithm has been developed to design the nonlinear frequency modulated (NLFM) signal for the four windows of Raised-Cosine, Taylor, Chebyshev, and Kaiser. We have already designed NLFM signal by stationary phase method. The simulation results for the peak sidelobe level of the autocorrelation function in the phase improvement algorithm reveal a significant average decrement of about 5 dB with respect to stationary phase method. Moreover, to evaluate the efficiency of the phase improvement algorithm, minimum error value for each iteration is calculated.
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PDF链接：
https://arxiv.org/pdf/1804.06899

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关键词：自相关函数 相关函数 自相关 Applications Optimization 波形 improvement 中自 algorithm 评价