基于自适应滤波的微弱GPS信号跟踪方法

摘要

针对全球定位系统(GPS)传统跟踪算法在接收信号很微弱的条件下跟踪误差大,为保持跟踪精度,提出了一种新的跟踪方法.同时考虑了多普勒频移和码相位偏移量作为观测模型,然后采用自适应卡尔曼滤波算法,有效减轻了系统噪声和观测噪声对信号跟踪的影响；并通过列文伯格-马夸尔特方法,优化迭代过程,进一步提高自适应卡尔曼滤波算法的稳定性和收敛速度.仿真结果显示,利用新的算法对载噪比低至21dB-Hz的微弱GPS信号取得了良好的跟踪精度和极高的灵敏度.%Traditional tracking method is difficult to track weak GPS signals and has a high probability of losing lock.In order to solve the problem,a new tracking method was proposed.This work considered both the Doppler shift and code phase delay in the measurement model and adaptive Kalman filter to reduce the impact of noise.Also,Levenberg-Marquardt method was implemented for iterative process optimization to improve the stability and convergence rate of the adaptive Kalman filter algorithm.The simulation results show that the new method can maintain lock on a signal as weak as 21dB-Hz with high tracking accuracy and sensitivity.