| 引用本文: | 王海峰，行鸿彦，孙江，苏新. 基于差分进化的随机共振混沌小信号检测[J]. 雷达科学与技术, 2022, 20(5): 531-538.[点击复制] |
| WANG Haifeng, XING Hongyan, SUN Jiang, SU Xin. Detection of Stochastic Resonance Chaotic Small Signal Based on Differential Evolution[J]. Radar Science and Technology, 2022, 20(5): 531-538.[点击复制] |
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| 摘要: |
| 针对传统随机共振小信号检测无法对多参数进行同步调优的缺陷，本文提出了一种基于变种差分进化算法的随机共振混沌小信号检测方法。利用变种差分进化算法对Duffing振子的随机共振系统参数进行寻优，以系统输出信噪比为寻优问题的目标函数。为了验证算法的可行性，分别进行低频和高频小信号输入的仿真实验，在低频小信号检测实验中，输出信噪比较混沌变步长萤火虫优化算法平均提升1.98dB；高频小信号检测实验中，结合外差式随机共振理论，能够准确恢复出高频小信号对应低频段处的小信号，进一步推导出高频小信号的存在；对实测海杂波数据进行仿真实验，实验结果表明该方法能够有效地检测出淹没在海杂波背景下的混沌小信号。 |
| 关键词: 混沌小信号 变种差分进化算法 随机共振 微弱信号检测 海杂波 |
| DOI：DOI:10.3969/j.issn.1672-2337.2022.05.009 |
| 分类号:TN911.7 |
| 基金项目:国家重点研发计划资助项目（No.2021YFE0105500）；国家自然科学基金（No.62171228） |
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| Detection of Stochastic Resonance Chaotic Small Signal Based on Differential Evolution |
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WANG Haifeng, XING Hongyan, SUN Jiang, SU Xin
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1. Jiangsu Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;2. College of IoT Engineering, Hohai University, Changzhou 213022, China
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| Abstract: |
| Aiming at the defect that the traditional stochastic resonance small signal detection cannot synchronously tune multiple parameters, a chaotic small signal detection method based on the variant differential evolution algorithm is proposed in this paper. Variant differential evolution algorithm is used to optimize the parameters of stochastic resonance system of Duffing oscillator. The SNR of system output is taken as the objective function. In order to verify the feasibility of the algorithm, the simulation experiments of low frequency and high frequency small signal input were carried out respectively. In the low frequency small signal detection experiment, the output SNR is improved 1.98 dB on average compared to the chaotic variable step size firefly optimization algorithm. In the high-frequency small signal detection experiment, combined with heterodyne stochastic resonance theory, the high-frequency small signal corresponding to the small signal in the low-frequency band can be accurately recovered, and the existence of high-frequency small signal can be further deduced. Simulation experiments on sea clutter data show that this method can effectively detect small chaotic signals submerged in sea clutter background. |
| Key words: chaotic small signal variant differential evolution algorithm stochastic resonance weak signal detection sea clutter |
