基于FRFT的天波雷达多机动目标检测
发布时间：2018-11-10 08:35
【摘要】：天波超视距雷达(over-the-horizon radar,OTHR)中,机动目标信号存在频谱扩展,导致目标检测性能下降。强的海杂波进一步增加了机动目标的检测难度。针对该问题,考虑到海杂波信号能量主要集中在零频附近,而且可以建模为一个自回归(auto-regressive,AR)过程,用AR滤波器抑制海杂波;考虑到机动目标信号近似为线性调频信号,而分数阶傅里叶变换(fractional Fourier transform,FRFT)能有效积累线性调频信号的能量,因此采用FRFT算法估计目标运动参数,实现机动目标检测;在此基础上用分级迭代的FRFT进一步降低运算量;针对多目标检测问题,用"CLEAN"方法逐个检测机动目标。仿真结果表明,与已有的离散多项式变换(discrete polynomial transform,DPT)算法相比,本文算法可以更好地适用于多目标检测;与Radon-Wigner变换算法相比,本文算法可以达到更高的参数估计精度。
[Abstract]:In sky-wave over-the-horizon radar (over-the-horizon radar,OTHR), the spectrum spread of maneuvering target signal leads to the degradation of target detection performance. Strong sea clutter further increases the difficulty of maneuvering target detection. To solve this problem, considering that the energy of sea clutter is mainly concentrated near zero frequency, and can be modeled as an autoregressive (auto-regressive,AR) process, AR filter is used to suppress sea clutter. Considering that the maneuvering target signal is approximately linear frequency modulation (LFM) signal and fractional Fourier transform (fractional Fourier transform,FRFT) can effectively accumulate the energy of LFM signal, the moving parameters of maneuvering target are estimated by FRFT algorithm to realize maneuvering target detection. On this basis, the computational complexity is further reduced by using the hierarchical iterative FRFT, and the "CLEAN" method is used to detect the maneuvering targets one by one for the multi-target detection problem. The simulation results show that compared with the existing discrete polynomial transform (discrete polynomial transform,DPT) algorithm, the proposed algorithm is more suitable for multi-object detection, and the proposed algorithm can achieve higher parameter estimation accuracy than the Radon-Wigner transform algorithm.
【作者单位】： 电子科技大学电子工程学院;
【基金】：国家自然科学基金重点项目(61032010,61371184,61101172) 中央高校基本科研业务费专项资金(ZYGX2012J018)资助课题
【分类号】：TN958.93
[Abstract]:In sky-wave over-the-horizon radar (over-the-horizon radar,OTHR), the spectrum spread of maneuvering target signal leads to the degradation of target detection performance. Strong sea clutter further increases the difficulty of maneuvering target detection. To solve this problem, considering that the energy of sea clutter is mainly concentrated near zero frequency, and can be modeled as an autoregressive (auto-regressive,AR) process, AR filter is used to suppress sea clutter. Considering that the maneuvering target signal is approximately linear frequency modulation (LFM) signal and fractional Fourier transform (fractional Fourier transform,FRFT) can effectively accumulate the energy of LFM signal, the moving parameters of maneuvering target are estimated by FRFT algorithm to realize maneuvering target detection. On this basis, the computational complexity is further reduced by using the hierarchical iterative FRFT, and the "CLEAN" method is used to detect the maneuvering targets one by one for the multi-target detection problem. The simulation results show that compared with the existing discrete polynomial transform (discrete polynomial transform,DPT) algorithm, the proposed algorithm is more suitable for multi-object detection, and the proposed algorithm can achieve higher parameter estimation accuracy than the Radon-Wigner transform algorithm.
【作者单位】： 电子科技大学电子工程学院;
【基金】：国家自然科学基金重点项目(61032010,61371184,61101172) 中央高校基本科研业务费专项资金(ZYGX2012J018)资助课题
【分类号】：TN958.93
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