基于自适应步长萤火虫-多重信号分类算法的低空目标波达方向估计

周豪; 胡国平; 汪云

doi:10.12000/JR14142

基于自适应步长萤火虫-多重信号分类算法的低空目标波达方向估计

DOI: 10.12000/JR14142

(空军工程大学防空反导学院西安 710051)

基金项目:

国家自然科学基金(61372166)和陕西省自然科学基础研究计划(2014JM8308)资助课题

详细信息

作者简介:
周豪(1990-),男,河南南阳人,硕士研究生在读,主要研究方向为低空目标探测.E-mail:15339216717@163.com胡国平(1964-),男,江西南昌人,教授,博士生导师,主要研究方向为雷达信号处理.E-mail:hgp9162@163.com汪云(1989-),男,江西上饶人,博士研究生在读,主要研究方向为低空目标探测.E-mail:yunyingxikuang@163.com

通讯作者:
周豪15339216717@163.com

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出版历程
- 收稿日期: 2014-11-25
- 修回日期: 2015-04-28
- 网络出版日期: 2015-06-28

DOA Estimation of Low Altitude Target Based on Adaptive Step Glowworm Swarm Optimization-multiple Signal Classification Algorithm

Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China

摘要

摘要: 该文针对传统多重信号分类算法(MUSIC)不适用于低空多径环境下目标波达方向(DOA)估计且谱峰搜索计算量大的问题,在解相干基础上,提出一种基于自适应步长萤火虫算法的多重信号分类算法.该方法通过对快拍数据协方差矩阵虚拟平滑实现多径信号的完全解相干和满秩相关矩阵的构造,利用自适应步长萤火虫算法实现谱峰搜索和目标角度估计.仿真结果表明,新方法能够在无孔径损失的情况下较好克服低空多径效应影响,快速、精确地估计目标波达方向.
- 多重信号分类算法 /
- 解相干 /
- 自适应步长萤火虫算法
Abstract: The traditional MUltiple SIgnal Classification (MUSIC) algorithm requires significant computational effort and can not be employed for the Direction Of Arrival (DOA) estimation of targets in a low-altitude multipath environment. As such, a novel MUSIC approach is proposed on the basis of the algorithm of Adaptive Step Glowworm Swarm Optimization (ASGSO). The virtual spatial smoothing of the matrix formed by each snapshot is used to realize the decorrelation of the multipath signal and the establishment of a fullorder correlation matrix. ASGSO optimizes the function and estimates the elevation of the target. The simulation results suggest that the proposed method can overcome the low altitude multipath effect and estimate the DOA of target readily and precisely without radar effective aperture loss.
- MUSIC algorithm /
- De-correlation /
- Adaptive Step Glowworm Swarm Optimization (ASGSO)

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参考文献(15)

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