基于EMD算法的空间自旋目标平动补偿与微动特征提取

针对微多普勒频率附加在空间目标高速轨道运动产生的多普勒频移上使微动特征提取更加困难这一问题,提出了一种利用EMD算法对空间目标进行精确平动补偿和微多普勒特征提取的方法。对空间自旋目标进行建模,推导了窄带雷达条件下空间目标的微多普勒效应,并分析了平动分量对微多普勒的影响;把目标回波分解成一系列本征模态函数(IMF),然后求出瞬时频率,利用经验模型分解(EMD)算法对瞬时频率进行分解,分析各分量的能量百分比判别平动频移分量,实现回波信号的平动补偿;对平动补偿后的信号利用 EMD算法分离出微多普勒曲线,提取微动特征。仿真实验验证了该方法的可行性与有效性。

Translational Motion Compensation and Micro-Doppler Characteristic Extraction for Space Spinning Target Based on EMD Algorithm

Aimed at the difficulty, in the micro-Doppler characteristic extraction, caused by the Doppler frequency produced by high-speed trajectory movement of space target to which the micro-Doppler frequency is added, a method is proposed in this paper based on EMD algorithm to achieve translational motion compensation accurately and extract micro-Doppler characteristics. Firstly, the micro-Doppler effect of space spinning target in narrowband radar is deduced and the influence of translational motion on micro-Doppler is analyzed. Secondly, the radar echoes are decomposed into a series of intrinsic-mode functions (IMFs), and the EMD algorithm is used to decompose the instantaneous frequency of the IMFs. The translational motion compensation can be achieved by judging the translational frequency shift component and analyzing the power of IMFs. Finally, the micro-Doppler curves are separated and the micro-motion features of space target such as spinning frequency are also obtained based on the EMD algorithm. Simulations show that the proposed algorithm is feasible and effective.