基于极化不变量的谐波雷达导引头目标识别算法

为解决基于目标谐波散射系数的FFT识别算法无法有效识别目标全弹道谐波散射特性的问题，采用了基于极化不变量的目标识别算法.根据目标的半导体模型拟合出目标的谐波散射系数，用卡尔曼滤波器对谐波散射系数进行估计.将估计结果作为酉矩阵的对角元素，建立了目标谐波极化散射矩阵及与其对应的功率矩阵，通过就不同的目标进行谐波散射极化计算得到了仿真结果.结果表明，与基于目标谐波散射系数的FFT识别算法相比，目标谐波极化散射矩阵行列式的值及功率矩阵的迹能反映出目标的全弹道谐波散射特性，二者可以作为有效的目标识别特征量. 

Harmonic Wave Radar Seeker Target Recognition Algorithm Based on Polarization Invariant

Traditional FFT recognition algorithm based on harmonic wave scattering coefficient could not effectively distinguish the whole trajectory harmonic wave scattering properties of targets. To solve this problem, target recognition algorithm based on polarization invariant was proposed. The target''s harmonic wave scattering coefficient was deduced according to its semiconductor model. The target''s harmonic wave scattering coefficient was estimated using Kalman filter. With the estimated coefficient as the diagonal element of the unitary matrix, target harmonic wave polarization scattering matrix and harmonic wave power matrix were built. Simulation results were obtained through the harmonic wave scattering polarization algorithm of different targets. The results show that this algorithm can reflect the whole trajectory harmonic wave scattering properties of the target compared with FFT recognition algorithm based on harmonic wave scattering coefficient and that the value of the target''s harmonic wave polarization scattering matrix and the trajectory of the power matrix could be used as effective characteristic variables for target recognition.