摘要
针对卫星导航信号容易受到窄带干扰影响而降低导航性能的问题,提出了一种基于神经网络的全球定位系统接收机抗干扰方法.该方法通过自适应陷波器与反向传播神经网络级联,利用二阶格型无限脉冲响应自适应陷波器滤除带外干扰,再结合反向传播神经网络预测器来估计并消除干扰.从捕获卫星数、信噪比提升值和迭代次数对算法性能进行仿真比较,结果表明,文中方法可有效抑制窄带干扰,并且有更强的抗窄带能力、更快的收敛速度.
Satellite navigation suffers from performance degradation in the presence of narrowband interference.We present a Global Positioning System(GPS)receiver anti-jamming algorithm based on the neural network.The method combines the adaptive notch filter with the Back Propagation(BP)neural network.We first use the two order lattice infinite impulse response adaptive notch filter to eliminate-outof-band jamming,then use the BP neural network predictor to estimate and cancel jamming.We analyze three aspects of algorithm performance which include acquired satellite numbers,signal-to-noise improvements and iteration numbers.Simulation results show that the method can effectively suppress narrowband interference and has a better anti-jamming capacity and a faster convergence speed.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2017年第6期116-121,共6页
Journal of Xidian University
基金
国家自然科学基金资助项目(61571370)
关键词
全球定位系统
神经网络
自适应陷波器
干扰
干扰抑制
global positioning system
neural networks
adaptive notch filter(ANF)
jamming
interference suppression
