基于Krylov子空间的多级维纳抗干扰滤波设计

全球卫星导航系统(GNSS, Global Navigation Satellites System)空时抗干扰要求有较好的实时处理能力,常规矩阵求逆的算法由于计算量太大限制了其在GNSS中的应用.在分析多级维纳滤波(MWF,Multi-stage nested Wiener Filter)原理的基础之上,结合Krylov子空间性质,设计出一种应用于GNSS空时抗干扰的自适应多级维纳滤波器,从而实现了在Krylov子空间中降维滤波,避免了矩阵求逆的大运算量.仿真结果表明,该算法在保证抗干扰性能不受影响的前提下,降低了GNSS空时抗干扰算法的计算量,提高了实时处理能力.

Design of multi-stage nested wiener filter employing Krylov subspace for anti-interference

Space and time anti-interference for global navigation satellites system(GNSS) receivers requires good real-time processing ability.This limits the application of conventional matrix inversion algorithms due to their large amount of computation.Based on the analysis of the principle of multi-stage wiener filtering and combined with Krylov subspace nature,a multi-stage Wiener filter was designed for GNSS receivers.In this way,a reduction of filtering dimensions in Krylov subspace was achieved and the intensive computation for matrix inversion was avoided.Simulation results show that the proposed method can effectively reduce the amount of STAP algorithm computation with no anti-interference performance being affected and is more appropriate for real-time applications.