Study of Threshold Setting for Rapid Detection of Multicomponent LFM Signals Based on the Fourth-Order Origin Moment of Fractional Spectrum

Study of Threshold Setting for Rapid Detection of Multicomponent LFM Signals Based on the Fourth-Order Origin Moment of Fractional Spectrum
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基于分数谱四阶原矩的多分量LFM信号快速检测阈值设置研究

DOI:
10.1007/s00034-012-9449-3
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发表时间:
2013-02
期刊:
Circuits, Systems, and Signal Processing
影响因子:
--
通讯作者:
Wang, Yiming
Wang, Yiming
中科院分区:
其他
文献类型:
--
作者:
Chen, Rong;Wang, Yiming

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分数阶傅里叶变换(FRFT)用于检测多分量线性调频(LFM)信号时,弱信号分量往往被强信号的旁瓣所掩盖,无法有效检测。CLEAN技术通过迭代地从多分量信号中减去检测到的强信号分量并对剩余信号应用检测算法来改善这种情况。因此,可以消除强分量的不利影响,并且可以检测弱信号分量。然而,由于在每次迭代中仅检测并减去最强的LFM分量,因此检测迭代的数量将与LFM分量的数量成正比。通过分析分数阶谱四阶原点矩(OMFrS)在不同LFM分量间的遮蔽关系,提出了一种基于遮蔽系数的多分量LFM信号快速检测阈值设置方法。该方法可以在一次迭代中同时检测出多个在各自最佳旋转角处的四阶OMFrS不被强分量遮挡的LFM分量。因此,检测迭代次数和计算复杂度显着减少。仿真结果验证了该方法的有效性。
By using Fractional Fourier Transform (FRFT) for detecting multicomponent linear frequency-modulated (LFM) signals, weak signal components are usually shadowed by the sidelobes of strong ones and cannot be detected effectively. The CLEAN technique is widely used to improve such a situation via subtracting the detected strong signal component from the multicomponent signals iteratively and applying detection algorithm to the remainder signals. Thus the adverse effect of strong components can be eliminated and weak signal components may be detected. However, since only the strongest LFM component is detected and subtracted in each iteration, the number of detection iteration will be directly proportional to the number of LFM components. Using concept of shading coefficient, a novel threshold setting method for rapid detection of multicomponent LFM signals has been proposed by analyzing the shading relation among the fourth-order origin moment of fractional spectrum (OMFrS) of different LFM components. By employing the proposed method, several LFM components whose fourth-order OMFrS at their own optimal rotation angles are not shadowed by strong components can be detected at the same time in one iteration. Consequently, the number of detection iteration and the computational complexity are reduced dramatically. Simulation results are given to verify that this new approach is valid.
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