| Suppressing Autocorrelation Sidelobes of LFM Pulse Trains with Genetic Algorithm |
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| 作者姓名： | 王鹏 孟华东 王希勤 |
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| 作者单位： | Intelligent Transportation Information Systems Laboratory，Department of Electronic Engineering，Tsinghua University |
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| 摘 要： | Modulations and diversities, including the Costas-ordered stepped-frequency and nonlinear stepped-frequency waveforms are widely used in linear frequency modulation （LFM） pulse trains to reduce the relatively high autocorrelation function （ACF） sidelobes. An efficient method was developed to optimize the interpulse frequency modulation to remove most of the ACF sidelobes about the mainlobe peak, with only a small increase in the mainlobe width. The genetic algorithm is used to solve the nonlinear optimization problem to find the interpulse frequency modulation sequence. The effects on the ACF sidelobes suppression and mainlobe widening are studied. The results show that the new design is superior to the corresponding stepped-frequency LFM signal and weighted stepped-frequency LFM signal in the terms of the ACF sidelobes reduction and mainlobe spread.
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| 关 键 词： | LFM脉冲 遗传算法 自相关函数 调制 多样性 |
| 收稿时间： | 20 August 2007 |
| 修稿时间： | 18 August 2008. |
Suppressing Autocorrelation Sidelobes of LFM Pulse Trains with Genetic Algorithm |
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| Peng Wang, ï, Huadong Meng, ¿ì,Xiqin Wang, ì.Suppressing Autocorrelation Sidelobes of LFM Pulse Trains with Genetic Algorithm[J].Tsinghua Science and Technology,2008,13(6):800-806. |
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| Authors: | Peng Wang ï Huadong Meng ¿ì Xiqin Wang ì |
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| Institution: | aIntelligent Transportation Information Systems Laboratory, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China |
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| Abstract: | Modulations and diversities, including the Costas-ordered stepped-frequency and nonlinear stepped-frequency waveforms are widely used in linear frequency modulation (LFM) pulse trains to reduce the relatively high autocorrelation function (ACF) sidelobes. An efficient method was developed to optimize the interpulse frequency modulation to remove most of the ACF sidelobes about the mainlobe peak, with only a small increase in the mainlobe width. The genetic algorithm is used to solve the nonlinear optimization problem to find the interpulse frequency modulation sequence. The effects on the ACF sidelobes suppression and mainlobe widening are studied. The results show that the new design is superior to the corresponding stepped-frequency LFM signal and weighted stepped-frequency LFM signal in the terms of the ACF sidelobes reduction and mainlobe spread. |
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| Keywords: | coherent train autocorrelation function (ACF) sidelobes suppression genetic algorithm (GA) performance improvement |
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