一种针对GNSS接收机的宽零陷抗干扰算法

为解决干扰信号来向快速变化情况下,基于线性约束最小功率(linear constraint minimum power,LCMP)准则的传统抗干扰算法可能难以收敛,致使全球卫星导航系统(global navigation satellite system,GNSS)接收机失锁的问题,提出了一种基于协方差矩阵锥化(covariance matrix taper,CMT)的零陷加宽抗干扰算法,使变化的干扰信号来向能够始终保持在拓展的零陷之内.首先,在实际干扰信号来向变化不可预测的条件下,所提算法假设干扰信号来向变化服从三角形概率分布统计模型;然后,依据这一模型推导假设情况下的虚拟协方差矩阵与真实协方差矩阵的转换关系,再根据转换关系和真实采样协方差矩阵得到虚拟采样协方差矩阵.通过虚拟采样协方差矩阵求解阵列天线各通道权值;最后,将所提三角形分布算法与传统的均匀分布算法和拉普拉斯分布算法进行了对比分析.研究结果表明,该算法可以有效加宽在干扰信号来向上的零陷并抑制干扰,而且相比于均匀分布算法和拉普拉斯分布算法,三角形分布算法在形成零陷的宽度和深度一致性之间更加平衡,阵列输出信干噪比也要更高,最后结合软件接收机验证了所提算法的有效性.

A null widening anti-jamming algorithm for GNSS receivers

Since the directions of arrival (DOAs) of interferences change rapidly in high dynamic conditions, the traditional anti-jamming algorithm based on the linearly constrained minimum power (LCMP) criterion cannot suppress the interferences effectively, which may lead to the acquisition failure of GNSS receivers. To slove this problem, a covariance matrix taper (CMT) null widening algorithm was proposed, which can make the DOAs of interferences always in the widening nulls. Firstly, the DOAs of interferences which are unpredictable in practice were assumed to be triangular distributed. Then, the conversion relationship between the virtual covariance matrix and the real covariance matrix was obtained according to the assumption. Consequently, the virtual sample covariance matrix was derived, based on which the weight vector was acquired. Finally, the propsed algorithm was compared with the algorithms that adopt uniform distribution model and Laplace distribution model. The research results show that the proposed algorithm can widen the nulls effectively. Compared with uniform distribution model and Laplace distribution model, the proposed model achieved a superior balance between the null width and the null depth, and it had a higher array output signal to interference plus noise ratio (SINR). Moreover, software GNSS receiver was used to validate the effectiveness of the proposed algorithm.