基于微动调制的梳状谱灵巧噪声压制干扰

针对目前相干压制干扰算法干扰面积不足、非相干压制干扰算法发射功率要求高等问题，本文在噪声卷积干扰及微动干扰算法的基础上，提出一种基于微动调制的梳状谱灵巧噪声压制干扰算法。该算法能够在距离向及方位向获得部分压缩增益，降低了对干扰机发射功率的需求，同时在压制干扰面积上优于其他干扰算法，可根据压制区域地物回波特性对干扰参数进行调整，达到干扰要求。此外，针对图像客观评估中没有考虑人眼主观因素影响的不足，本文采用了基于人眼视觉特性的主、客观结合的图像评估指标对干扰前后的图像进行评估。场景实测数据与干扰信号仿真数据结合后得到的图像评估结果表明，本文所提出的干扰算法能够在一片区域中形成有效的面状压制干扰，且适用场景广泛，可以实现对面目标的有效保护。

Suppression Jamming of Comb Spectrum Smart Noise Based on Micro-Motion Modulation

Aiming at the problem that the jamming area of the current coherent suppression jamming algorithm is not big enough and the transmitting power requirement of the non-coherent suppression jamming algorithm is high, a comb spectrum smart noise convolutional suppression jamming algorithm based on micro-motion modulation is proposed in the present study. This algorithm can obtain partial compression gain in the distance direction and azimuth direction, which reduces the demand for the transmitting power of the jammer. The algorithm is superior to other jamming algorithms in suppressing the jamming area, and the interference parameters can be adjusted according to the echo characteristics of ground objects in the suppression area to meet the interference requirements as well. In addition, as the subjective factors of human eyes are not considered in commonly used objective image evaluation methods, an image evaluation indicator combined with subjective and objective is adopted in this paper to evaluate the images before and after the jamming. The image evaluation results from testing and simulation data show that the proposed jamming algorithm can form an effective suppression jamming in a region, and can be widely used in the different scenes, which will effectively protect the target.