基于循环自相关/平均幅度差函数的弹道目标微动周期估计

雷达微多普勒(m-D)是弹道目标的突出特征,为弹头识别提供了重要手段.然而,当弹道目标的微动伴随平动时,时频分布不再表现为正弦调制曲线,此时基于时频分布正弦假设的微多普勒特征提取方法可能失效.针对这一问题,提出了一种循环自相关函数(CACF)和循环平均幅度差函数(CAMDF)相结合的估计算法,来获取时频分布的循环系数矩阵和该矩阵的平均循环系数,从而估计出弹道目标的微动周期.该算法以时频分布的循环周期性代替正弦调制的周期性,不需要假设目标平动已被准确补偿,有效克服了传统微动周期估计方法的不足.理论推导论证了该算法的可行性,仿真实验验证了该算法的有效性和抗噪性.

A Micro-Doppler Period Estimation of Ballistic Targets Based on Circular Autocorrelation and Average Magnitude Difference Function

Micro-Doppler (m-D) in ballistic targets is characterized by applying an important means to warhead recognition. However, when the micro motion of the ballistic targets is accompanied by macro motion, the time frequency representation is no longer a sinusoidal modulation curve. Aimed at the problem that the micro Doppler feature extraction method based on the sinusoidal hypothesis of time frequency representation may become ineffective, an estimation algorithm based on circular autocorrelation function (CACF) in combination with the circular average amplitude difference function (CAMDF) is proposed to obtain the circular coefficient matrix of time frequency representation and average circular coefficients of the matrix, estimating the m D period of ballistic targets. The algorithm does not need to assume with the target macro motion having been accurately compensated and the shortcomings of traditional m D period estimation methods having been overcome effectively. The feasibility of the algorithm is demonstrated by theoretical derivation, and the effectiveness and anti noise of the algorithm is verified by simulation experiments.