| 基于分时双频的高频地波雷达海面目标探测 |
| |
| 引用本文： | 熊俊志,杨子杰,王勤.基于分时双频的高频地波雷达海面目标探测[J].华中科技大学学报(自然科学版),2007,35(6):34-37. |
| |
| 作者姓名： | 熊俊志 杨子杰 王勤 |
| |
| 作者单位： | 武汉大学,电子信息学院,湖北,武汉,430079 |
| |
| 基金项目： | 国家高技术研究发展计划(863计划) |
| |
| 摘 要： | 提出了一种分时双频方法用以提高其目标探测性能.分析了分时双频雷达波形,针对分时双频探测引起的目标相干积累时间减少以及多普勒谱点不对齐等问题,利用非均匀傅里叶变换将其转换为一不适定问题,并利用Cauchy-Gaussian模型正则化方法进行外推处理,从而获得目标多普勒谱图.仿真结果表明该方法能够有效地消除海面移动目标的检测盲区,提高检测性能.
|
| 关 键 词： | 高频地波雷达 分时双频 目标检测 正则化非均匀外推 双频探测 高频地波 达海 目标探测 dual frequency based HF ground wave radar sea surface 检测性能 检测盲区 移动目标 正则化方法 仿真结果 谱图 处理 外推 模型 不适定问题 转换 傅里叶变换 |
| 文章编号： | 1671-4512（2007）06-0034-04 |
| 修稿时间： | 2006-03-07 |
Detection of targets on the sea surface using HF ground wave radar based on time-division dual frequency |
| |
| Xiong Junzhi,Yang Zijie,Wang Qin.Detection of targets on the sea surface using HF ground wave radar based on time-division dual frequency[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,2007,35(6):34-37. |
| |
| Authors: | Xiong Junzhi Yang Zijie Wang Qin |
| |
| Institution: | School of Electronic Information, Wuhan University, Wuhan 430079, China |
| |
| Abstract: | When slow-speed targets are detected by HF ground wave radar,there would be some blind zones because of first-order sea clutters.A method is proposed to improve the targets detection using time-division dual frequency(TDDF).TDDF radar waveforms were analyzed.For the problems of the reduction of targets coherent integration time(CIT) and the mismatch of Doppler spectrum caused by the detection using TDDF,the paper introduces NDFT to transforming it to an ill-posed problem.Then the targets Doppler spectrum could be acquired by extrapolation process based on Cauchy-Gaussian model regularization method.The simulation results show that the method can eliminate the blind areas of sea-surface moving targets detection effectively and enhance targets detestability largely. |
| |
| Keywords: | HF ground wave radar time-division dual frequency target detection regularized nonuniform extrapolation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
