基于并行单星约束的导航抗干扰研究

在全球定位系统中使用空时自适应处理算法可以增强接收机的抗干扰性能,为防止算法对卫星信号的衰减,可通过约束条件对卫星信号进行保护,传统的单星约束可以保证每颗卫星输出信噪比最大,但运算量很大。虽然多星约束可以使所有卫星的综合输出性能最优,且减少了运算量,但无法保证单颗卫星的输出信噪比性能。对空时自适应处理算法进行了合理简化,提出了并行单星约束算法,与多星约束相比,所提算法不仅运算量更小,还可保证每颗卫星输出信噪比最大。仿真结果表明,所提算法在对干扰信号进行抑制的同时,有效地实现了对多颗卫星信号的保护。

New constrained parallel single star algorithm for navigation interference suppression

The space time adaptive processing algorithms are able to enhance the performance of global positioning system （GPS） receiver interference suppression. The satellites signals can be protected by imposing the constraints on the STAP algorithm. Traditional constraints on a single star generates maximum signal-to-noise ratio of each satellite, however, the computation burden is too heavy for the real-time performance. Although the constraints on multiple satellites can ensure optimal output performance of all satellites, the optimal performance of a single satellite cannot be guaranteed. In this paper, by reasonably simplifying adaptive processing algorithm, a novel constrained parallel single star constraints algorithm is proposed to achieve much less computation burden. In contrast with the traditional algorithms of constraints on multiple satellites, the proposed algorithm yields optimal signal-to-noise ratio performance of all satellites. The simulation results show that the new algorithm can not only suppress interfering signals, but also protect the satellite signals more effectively.