面向线性调频干扰的空频自适应处理算法

Space-frequency adaptive processing algorithm for LFM interference

针对卫星导航应用中线性调频(linear frequency modulated,LFM)干扰统计特征时变引起的抗干扰性能下降问题,提出了一种基于数据空时频三维特征分组的空频自适应处理(space-frequency adaptive processing,SFAP)算法。首先通过时频分析方法获取采样数据的时域、频域联合分布,并利用空间相关系数分析相同频率干扰在不同时间的空间相关性,然后对SFAP的采样数据进行分组,将不同时间具有相同频率和到达角参数的采样点分到相同组,最后利用分组后的数据进行协方差矩阵估计、权值计算和自适应滤波,提高了干扰特征值、增加了零陷深度、提升了抗干扰能力。仿真结果表明,所提算法可有效提升卫星导航接收机对LFM干扰的抑制能力,且对存在单个和多个LFM干扰的场景均能适用。

Aiming at the problem of anti-jamming performance degradation caused by time-varying statistical characteristics of linear frequency modulated(LFM)interference in satellite navigation application,a space-frequency adaptive processing(SFAP)algorithm based on data grouping by space-time-frequency three-dimensional feature grouping is proposed.Firstly,the time-frequency analysis method is used to obtain the joint distribution of sampling data in time domain and frequency domain,and the spatial correlation coefficient is used to analyze the spatial correlation of the same frequency interference at different times.Secondly,the sampling data of SFAP are grouped,and the sampling points with the same frequency and direction of arrival(DOA)parameters at different times are divided into the same group.Finally,the covariance matrix estimation,weight calculation,and adaptive filtering are carried out by using the grouped data to improve the interference eigenvalue value,the null depth,and the anti-jamming ability.Simulation results show that the algorithm can effectively improve the suppression ability of satellite navigation receivers’LFM interference,and can be applied to the scene both with single LFM interference or multiple LFM interference.