一种卫星导航信号码跟踪环优化算法  

A Optimized Algorithm of Code Tracking Loop for Satellite Navigation Signals

作　　者：李基武 符强[1] 孙希延[1] 纪元法[1] 

机构地区：[1]桂林电子科技大学信息与通信学院,广西桂林541000

出　　处：《计算机仿真》2017年第1期52-56,共5页Computer Simulation

摘　　要：在微弱卫星信号跟踪优化的问题中,多径干扰和热噪声的抑制是码跟踪环的难点技术之一。针对解扩前最大似然多径估计算法在低信噪比时难以保证多径抑制和噪声消除效果的问题,提出了一种基于最大似然估计的ML-KF算法。通过采用最大似然估计对中频数据进行多径估计,恢复出接近真实值的估计直达信号,并用于后续的解扩处理;然后采用卡尔曼滤波算法,通过对各相关器的相关输出进行最优组合,通过建模,不断收敛码相位估计误差,给出了码相位时延的最佳估计值。仿真结果表明,在相同信噪比的条件下,提出的ML-KF估计算法跟踪精度较高。In the problem of optimization for weak satellite signal tracking, the mitigation of muhipath interference and thermal noise is one of the difficult technologies of code tracking loop. A ML-KF algorithm based on maximum likelihood estimation is proposed to reduce the effect of muhipath mitigation and noise in the case of low SNR. By using the maximum likelihood estimation to estimate the multipath element of intermediate frequency data, the estimated direct signal is recovered which is close to the true value, and then used for subsequent despread. The Kalman filtering algorithm is then employed to the optimal combination of correlator output, through modeling, the code phase estimation error is continuously convergent, the best estimation of the code phase delay is given. Simulation results show that, under the condition of same signal-to-noise ratio, the ML-KF estimation algorithm has more tracking precision than the algorithm of code tracking loop which only uses the maximum likelihood estimate.

关 键 词：全球定位系统 码跟踪环 卡尔曼滤波 多径 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]