建立频率步进连续波雷达摆动点目标回波模型,推导得出摆动目标高分辨距离像,研究距离像周期性变化规律,提出基于时间-距离像的摆动目标微动特征提取思路.针对幅度峰值搜索法对微摆动周期估计误差较大的问题,提出结合数据预处理的幅度峰值搜索法和幅度阈值检测法等两种改进算法.仿真实验表明,在信噪比高于-10 dB时,结合数据预处理的幅度峰值搜索法和幅度阈值检测法能够有效估计摆动目标距离、摆动幅度及摆动周期等参数,此时摆动幅度估计值是对其真实值在雷达视线方向上的投影值的估计.改进算法对目标距离和摆动幅度的估计精度与幅度峰值搜索法相同,对摆动周期的估计精度远远高于幅度峰值搜索法,可分别达到和优于采样周期的数量级.本文提出的改进算法可扩展应用于圆周旋转等周期性运动目标的微动特征提取.%The echo model of one-point vibrating target for stepped frequency continuous wave ( SFCW) radar is established first.Then high resolution range profile of the vibrating target is derived from the model. After the periodic laws of range profile of the target being analyzed , a micro-motion signature extraction method of vibrating targets based on time-range profiles is proposed. To improve the precision of the period estimation of micro-vibrating target extracted by the algorithm amplitude peak search ( APS) , two improved micro-motion signature extraction algorithms are camed out. One is data preprocessing based amplitude peak search ( DPBAPS) ; the other is amplitude threshold detection ( ATD) . Simulation experiments indicate that range , vibrating amplitude and vibrating period of the target can be achieved effectively by DPBAPS and ATD under the condition of that signal to noise ratio ( SNR) is above -10 dB,and the estimation of the vibrating amplitude is the estimation of the projection of the real vibrating amplitude onto the radar line of sight. The precision of the range and vibrating amplitude estimation of the two improved algorithms is the same as that of APS; however. the precision of the vibrating period estimation of the two improved algorithms is much higher than that of APS and can reach or be superior to the level of the sampling period. More over, the two improved algorithms put forward in this paper could be applied to other periodic moving targets such as rotary targets.
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