基于H/α极化分解的弹道目标鉴别

提出了一种基于H/α目标分解理论的弹道目标极化鉴别方法。首先简要给出了H/α目标分解理论的定义和数学模型,然后阐述了真实弹头和诱饵的不同微运动特性,即真弹头具有姿态控制故运动稳定,而诱饵由于没有姿态控制而出现旋转、翻滚等随机运动。在此基础上提取反映目标时间维散射随机性的极化特征量--时间熵。接着利用基于弹头模型暗室测量数据的弹道导弹全极化回波仿真方法,获取了不同战情下弹头与诱饵目标动态特性回波,进而对时间熵进行计算。实验表明,真弹头时间熵值与诱饵熵值可分性明显;时间熵与目标特性有关,但当诱饵与真弹头外形高度逼真时,该特征可有效鉴别真假目标;时间熵亦与所用数据长度(统计窗口)有关,但当统计窗口长度增加到进动周期时,时间熵趋于稳定。

Ballistic target discrimination based on H/α polarization decomposition

A novel approach for ballistic target discrimination based on H/α polarization target decomposition is addressed. Firstly, the definition and mathematical model of H/α target decomposition are introduced. Then the difference of micro-motion between real warheads and decoys, namely the movement of the warhead is more stable than decoys because of the attitude control, is described. On this basis, the method of extracting the feature, which is called time entropy and related with scattering randomness of ballistic target on the time dimension, is proposed. Then a fully-polarimetric radar echoes simulation procedure based on measurement data of warheads in the anechoic chamber, is intraduced. Thus, the radar echoes of warheads and decoys under different settings are gained so that the time entropy is then calculated. The experimental results show that the difference of the time entropy between the real warhead and decoy is obvious. The value of the time entropy is relevant with the target shape, but for the real warheads and decoys with the similar shape, the feature is valid. The proposed feature is also related with the data length (statistical window), however, when the data length is equivalent to the precession period, the value of the time entropy is stable.