在实际测量中,雷达散射截面积(RCS)往往具有趋势项、常值项、多周期等特点,为典型非平稳序列,目前RCS 序列周期估计主要为单目标、单周期简单仿真场景,尚缺乏一种适用于实测RCS 序列的高精度多周期估计方法。针对此问题,对快速傅里叶变换(FFT)谱分析和循环平均幅度差函数(CAMDF)等周期提取方法进行了分析研究,得出不同算法的适用性,并提出“FFT周期初判-数字滤波与信号分解-CAMDF单周期估计”的多周期估计方法。仿真和半物理仿真结果表明:该方法可融合FFT和CAMDF算法周期估计优点,有效解决了RCS序列多周期估计问题,具有较高估计精度和鲁棒性,工程应用价值较大。

The radar cross section (RCS) sequence actually measured by radar usually has trend item, constant item and multi-period, which is a typical non-stationary sequence. At present, the estimation method for RCS mainly aims at single target and single period by simple simulation calculation. An estimation method for multi-period RCS sequences is urgently needed for actual RCS sequence measured by radar. Aiming at this problem, fast Fourier transformation (FFT) method and circular average magnitude difference function (CAMDF) are studied to obtain the applicability for different algorithms and ‘FFT preliminary analysis-digital filtering and signal decomposition-CAMDF single period estimation’ method is put forward. Simulation and semi-physical simulation results show that the new method can combine advantages of the two algorithms, solving the period estimation problem of multiperiod RCS sequences effectively. The method has high estimation accuracy, robustness and great engineering application value.

TN957.51