Fast Non-Searching Method for Maneuvering Target Detection and Motion Parameters Estimation

Fast Non-Searching Method for Maneuvering Target Detection and Motion Parameters Estimation
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机动目标检测和运动参数估计的快速非搜索方法

DOI:
10.1109/tsp.2016.2515066
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发表时间:
2016-05
期刊:
IEEE Transaction on Signal Processing
影响因子:
--
通讯作者:
Cui Guolong
Cui Guolong
中科院分区:
其他
文献类型:
--
作者:
Li Xiaolong;Kong Lingjiang;Cui Guolong

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本文研究了机动目标检测和运动参数估计的相干积累问题,包括相干脉冲间隔内的距离徙动(RM)和多普勒频率徙动(DFM)。提出了一种基于相邻互相关函数(ACCF)和Lv分布(LVD)的快速非搜索方法,该方法首先利用相邻相关运算去除RM,降低DFM的阶数。在此基础上,利用LVD算法实现了相干积累、目标检测和参数估计。此外,在一定的性能损失的代价下,另一种快速的方法,通过ACCF迭代也被引入,以进一步降低计算复杂度和获得运动参数估计。所提出的两种方法是快速的,因为它们可以很容易地实现,通过使用复杂的乘法,快速傅立叶变换(FFT)和逆FFT(IFFT)。与现有方法相比,该算法无需搜索即可获得运动参数估计,并在计算量与检测能力和参数估计性能之间取得了较好的平衡。最后,通过仿真实验验证了该方法的有效性.
This paper considers the coherent integration problem for maneuvering target detection and motion parameters estimation, involving range migration (RM) and Doppler frequency migration (DFM) within the coherent pulse interval. A fast non-searching method based on adjacent cross correlation function (ACCF) and Lv's distribution (LVD) is proposed, where the adjacent correlation operation is first employed to remove the RM and reduce the order of DFM. After that, LVD is applied to realize the coherent integration, target detection and parameters estimation. In addition, at the cost of some performance loss, another fast method via ACCF iteratively is also introduced to further reduce the computational complexity and obtain the motion parameters estimation. The proposed two methods are fast in that they can be easily implemented by using complex multiplications, the fast Fourier transform (FFT) and inverse FFT (IFFT). Compared with the existing methods, the presented algorithms can obtain the motion parameters estimation without any searching procedure and can achieve a good balance between the computational cost and the detection ability as well as parameters estimation performance. Finally, several simulation experiments are provided to demonstrate the effectiveness.
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