低重频宽带雷达中小幅微动目标的周期估计

Micro-motion period estimation for targets with small LOS change in low PRF broadband radar

当空间微动目标仅发生小视角变化且雷达脉冲重复频率较低时,基于雷达散射截面序列、高分辨距离像(high-resolution range profile,HRRP)序列和微多普勒等特征提取算法的有效性面临了挑战。为此,基于宽带逆合成孔径雷达(inverse synthetic aperture radar,ISAR)像序列提出一种目标微动周期估计方法。基于微动目标ISAR成像的分析,利用ISAR图像序列之间的相似度进行微动周期估计。采用最小图像熵准则选取视线角线性变化区间的ISAR图像作为参考基准,利用图像动态范围压缩、基于全图像匹配的相似度估计等方法,强化算法稳定性并减小计算量。该方法对HRRP数据率要求低,对ISAR成像质量约束小,有利于工程实现。仿真实例从摆动和进动两种情况,分析了基准图像的选取和信噪比对算法性能的影响,证明了算法的有效性和高稳定性。

The radar cross section,high-resolution range profile（HRRP）and micro-Doppler based feature extraction algorithm may be invalid in the case of small changes line-of-sight（LOS）targets with low radar pulse repetition frequency.A micro-motion period estimate algorithm based on the periodic matching feature of inverse synthetic aperture radar（ISAR）image sequence is proposed.Based on the analysis of ISAR imaging of micromotion targets,we use the similarity between the images of ISAR sequence to estimate the micro-motion period.By using the minimum-entropy based criterion to select the base-image with linear LOS change and the methods of dynamic range compression and full image matching based similarity estimation,the algorithm achieves high stability and low computational complexity.And the algorithm has low constraints for the radar data rate and ISAR imaging quality which is suitable for engineering accomplishment.The simulation shows the validity and high stability of the estimation algorithm in the wobble and precession cases.The influence of the base-image selection and signal-to-noise ratio is also analyzed.