基于高阶模糊函数的进动目标平动补偿

Translational Motion Compensation of Precession Target Based on High-order Ambiguity Function

针对当前平动补偿算法存在的精度不高、稳定性较差的问题,提出了基于高阶模糊函数的进动目标平动补偿算法。该算法将平动引起的距离变化等效为三阶多项式,通过对回波各阶模糊函数进行峰值搜索,实现对各阶平动参数和微动周期的有效估计,进而实现对平动的补偿。仿真实验验证表明,该算法能够实现精确稳定的补偿,为后续基于微多普勒的弹道目标特征提取打下基础。

To solve the problem that current algorithms for translational compensation have low precision and poor stability,a compensation algorithm was proposed based on High-order Ambiguity Function (HAF) in this paper.The algorithm was equivalent to the distance change caused by translation to the third-order polynomial,after performing peaks search on every order's ambiguity function of the echo,the effective estimation of the translation parameters and the micro-motion period of each order were realized,and the compensation for translation was realized.The simulation experiment proved that the algorithm could achieve accurate and stable compensation,and set up the foundation for ballistic target feature extraction based on micro-Doppler.