| 引用本文: | 孙康,金钢,朱晓华,等.基于Q-MMSPF的海杂波多重分形互相关分析和目标检测.[J].国防科技大学学报,2013,35(3):170-175.[点击复制] |
| SUN Kang,JIN Gang,ZHU Xiaohua,et al.Multifractal cross-correlation analysis of sea clutter and target detection based on Q-MMSPF[J].Journal of National University of Defense Technology,2013,35(3):170-175[点击复制] |
|
| |
|
|
| 本文已被：浏览 7797次 下载 6111次 |
| 基于Q-MMSPF的海杂波多重分形互相关分析和目标检测 |
| 孙康1, 金钢2,3, 朱晓华1, 孙理1 |
|
(1.南京理工大学 电子工程与光电技术学院，江苏 南京 210094;2.中国空气动力研究与发展中心，四川 绵阳 621000;3.
3.电子科技大学 自动化工程学院，四川 成都 611731)
|
| 摘要: |
| 提出一种研究长程互相关和多重分形的新方法——Q阶混合矩结构分割函数法（Q-MMSPF），并利用Q-MMSPF分析了海杂波时间序列的多重分形互相关特征。通过对实测海杂波数据的计算分析发现，海杂波互相关多重分形特征较弱，目标信号之间的互相关多重分形特征明显，而目标信号与海杂波之间的互相关多重分形程度介于二者之间。据此，本文采用一种新的特征值进行海杂波背景下的目标检测。通过对不同条件下的实测海杂波数据验证，表明使用本文提出的特征值测量方法可以十分有效地检测出海杂波背景下的小弱目标。 |
| 关键词: 海杂波 多重分形互相关分析 Q阶混合矩结构分割函数法 目标检测 |
| DOI： |
| 投稿日期：2012-09-28 |
| 基金项目:江苏省科技厅科技专项（sbl201230101） |
|
| Multifractal cross-correlation analysis of sea clutter and target detection based on Q-MMSPF |
| SUN Kang1, JIN Gang2,3, ZHU Xiaohua1, SUN Li1 |
|
(1.School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China;2. China Aerodynamics Research and Development Center, Mianyang 621000, China;3. School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China)
|
| Abstract: |
| A novel method, the Qth order Mixed Moment Structure Partition Function (Q-MMSPF) method, is proposed for the detection of long range cross- correlations and multifractality. With this method, the multifractal cross-correlation characteristic of sea clutters was investigated. The analysis, based on the real sea clutter data, shows that the cross-correlation multifractality is quite weaker between the two sea clutter series, and the multifractality is significant between two time series of target plus sea clutter, whereas the multifractality is in the middle for the case, which is between target time series and sea clutter time ones. Consequently, an approach was suggested to detect the targets in sea clutter. The test results show that the target can be clearly distinguished from the sea clutter background with the proposed feature-based method. |
| Keywords: sea clutter multifractal cross-correlation analysis Qth order mixed moment structure partition function target detection |
|
|
|
|
|
