基于吕氏分布的机动目标参数化平动补偿方法

Parametric translational compensation method for maneuvering target based on Lv’s distribution

在逆合成孔径雷达(inverse synthetic aperture radar,ISAR)成像过程中,目标为规避雷达照射通常会进行机动,导致回波包络产生剧烈弯曲,同时加剧回波相位变化的复杂性,大大提升了平动补偿的难度。为了实现对机动目标回波进行准确稳定的平动补偿,提出一种基于吕氏分布(Lv’s distribution,LVD)的参数化平动补偿方法。首先将机动目标回波信号建模为多项式相位信号,利用相位差分对回波能量进行聚集,然后采用LVD和最小图像熵准则估计信号参数,最后构造补偿函数对回波的包络和相位误差进行同时补偿。实测数据实验证明了所提方法的有效性、优越性和低信噪比环境下的稳定性。

In the imaging process of inverse synthetic aperture radar(ISAR),the target usually maneuver to avoid radar exposure,which will cause the echo envelope to be severely curved.At the same time,it will aggravate the complexity of the echo phase change,which greatly improves the difficulty of translational compensation.In order to achieve accurate and stable translational compensation for maneuvering target echo,a parametric translational compensation method based on Lv’s distribution(LVD)is proposed.Firstly,models the maneuvering target’s echo is modeled as a polynomial phase signal,the phase difference is used to gather the echo energy.Then,the LVD and the minimum image entropy criterion are adopted to estimate the translational parameters.Finally,the compensation functions are founded to simultaneously compensate the envelope and phase errors of the echo.Experiments with measured data prove the effectiveness,superiority and stability of the proposed method under low signal to noise ratio environments.