基于零陷展宽并加深的高动态GNSS 抗干扰算法

为解决高动态下自适应抗干扰算法在零陷展宽后深度变浅的问题，提出了干扰扰动服从高斯统计分布的 零陷展宽并加深算法。该算法通过投影变换方法对数据进行预处理，提取采样信号中的干扰分量，并通过系数 加权增强干扰分量，在零陷展宽算法基础上构造新的协方差矩阵，最后利用功率倒置算法完成干扰抑制，达到 零陷展宽并加深的目的。仿真实验结果表明，在高动态条件下，所提算法在零陷展宽算法的基础上实现了深度 的增加，提高了零陷展宽抗干扰算法的稳健性。

High Dynamic GNSS Anti-Jamming Algorithms Based on Nulling Widening and Deepening#br#

In order to solve the problem that the depth of the adaptive anti-jamming algorithm becomes shallow after the null-pit broadening under high dynamic conditions，a null-pit broadening and deepening algorithm is proposed，in which the disturbance obeys the Gauss statistical distribution． The algorithm preprocesses the data by projection transformation，extracts the interference components from the sampled signal，enhances the interference components by weighting the coefficients，constructs a new covariance matrix on the basis of the null-pitch broadening algorithm，and finally uses the power inversion algorithm to suppress the interference to achieve the purpose of null-pitch broadening and deepening． The simulation results show that under high dynamic conditions，the depth of the proposed algorithm is increased on the basis of the null broadening algorithm，and the robustness of the null broadening anti-jamming algorithm is improved．