The high maneuvering target with jerk motion detection suffers from range migration (RM) and Doppler frequency migration (DFM). In this paper, the fourth order polynomial signal model is used to model the radar echo signal, and a novel high maneuvering target detection method is proposed. The RM is eliminated with Keystone transform (KT) and acceleration searching, and then the aligned echoes are extracted. With two defined symmetric autocorrelation functions (SAF) and the scaled Fourier transform, the third and fourth order motion parameters are estimated. Based on the estimated high order motion parameters, the fourth order polynomial phase signal is turned into linear frequency modulated (LFM) signal. To estimate the chirp rate of the LFM signal, a fast implementation method of second order Wigner Ville Distribution (SoWVD), named frequency domain SoWVD (FDSoWVD) is proposed. Based on the triple estimated motion parameters, the DFM is compensated and then the coherent integration can be achieved by fast Fourier transform, followed which the detection process is performed. Compared with other representative algorithms, the proposed method achieves a good balance between the computation complexity and detection ability. The effectiveness of the proposed method is verified by experiment with synthetic and raw data.

中文翻译：

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高机动目标加加速度运动参数估计与相干积分算法

具有急动运动检测的高机动目标会遭受距离偏移（RM）和多普勒频率偏移（DFM）的影响。本文采用四阶多项式信号模型对雷达回波信号进行建模，提出了一种新颖的高机动目标检测方法。通过梯形变换（KT）和加速度搜索消除RM，然后提取对准的回波。通过两个定义的对称自相关函数 (SAF) 和缩放傅立叶变换，可以估计三阶和四阶运动参数。基于估计的高阶运动参数，四阶多项式相位信号被转换为线性调频（LFM）信号。为了估计LFM信号的线性调频频率，提出了一种二阶Wigner Ville分布(SoWVD)的快速实现方法，称为频域SoWVD(FDSoWVD)。基于三重估计的运动参数，对DFM进行补偿，然后通过快速傅里叶变换实现相干积分，然后进行检测过程。与其他代表性算法相比，该方法在计算复杂度和检测能力之间取得了良好的平衡。通过合成数据和原始数据的实验验证了该方法的有效性。