Micro-motion Recognition of Spatial Cone Target Based on ISAR Image Sequences

ABSTRACT The accurate micro-motions recognition of spatial cone target is the foundation of the characteristic parameter acquisition. For this reason, a micro-motion recognition method based on the distinguishing characteristics extracted from the Inverse Synthetic Aperture Radar (ISAR) sequences is proposed in this paper. The projection trajectory formula of cone node strong scattering source and cone bottom sliptype strong scattering sources, which are located on the spatial cone target, are deduced under three micro-motion types including nutation, precession, and spinning, and the correctness is verified by the electromagnetic simulation. By comparison, differences are found among the projection of the scattering sources with different micro-motions, the coordinate information of the scattering sources in the Inverse Synthetic Aperture Radar sequences is extracted by the CLEAN algorithm, and the spinning is recognized by setting the threshold value of Doppler. The double observation points Interacting Multiple Model Kalman Filter is used to separate the scattering sources projection of the nutation target or precession target, and the cross point number of each scattering source’s projection track is used to classify the nutation or precession. Finally, the electromagnetic simulation data are used to verify the effectiveness of the micro-motion recognition method.

摘要 空间锥体目标的高精度微动识别是特征参数获取的基础。为此，本文提出了一种基于逆合成孔径雷达（Inverse Synthetic Aperture Radar，ISAR）序列提取区分特征的微动识别方法。针对空间锥体目标上的锥顶强散射源与锥底滑动型强散射源，本文推导了章动（nutation）、进动（precession）及自旋（spinning）三种微动模式下的投影轨迹公式，并通过电磁仿真验证了公式的正确性。通过对比不同微动模式下散射源投影轨迹的差异，本文采用CLEAN算法提取逆合成孔径雷达序列中散射源的坐标信息，并通过设置多普勒（Doppler）阈值实现自旋微动的识别。采用双观测点交互式多模型卡尔曼滤波器（Interacting Multiple Model Kalman Filter）分离章动目标或进动目标的散射源投影轨迹，并通过各散射源投影轨迹的交叉点数实现章动与进动的分类识别。最后，通过电磁仿真数据验证了所提微动识别方法的有效性。