基于空时降维处理的高动态零陷加宽算法

空时自适应处理是卫星导航抗干扰的有效方法。但在高动态环境下，干扰来向动态变化，干扰很容易移出常规自适应抗干扰算法所形成的窄零陷，导致算法失效。常用的解决办法是加宽零陷。该文从干扰来向变化的统计模型出发，提出一种基于拉普拉斯分布的空时加宽零陷算法，该算法能在干扰方向形成较宽的零陷。并且考虑到空时处理将增加算法的计算复杂度，该文将新的空时加宽零陷算法与多级维纳滤波器相结合，给出一种基于空时降维处理的加宽零陷算法。新算法能有效降低算法复杂度，并能在小快拍下得到更好的性能。仿真结果表明新算法的有效性。

A High-dynamic Null-widen Algorithm Based on Reduced-dimension Space-time Adaptive Processing

Space-Time Adaptive Processing (STAP) is effective to suppress wideband jammers in satellite navigation system. But in high-dynamic environment, the conventional STAP anti-jamming algorithms are invalid since jammers may easily move out of the array pattern null so that it can not be suppressed. In this paper, a new method of STAP null-widen is deduced based on Laplace distribution model of the changing interference DOA in high-dynamic environment. This method can broaden the width of nulls. But because of using of STAP, the amount of computation is increased significantly, a STAP null-widen method based on reduced-dimension Multistage Wiener Filters (MWF) is given in this paper. The effectiveness of the new method is proved in simulation part.