类卡尔曼无偏FIR滤波器改进高动态条件下载波跟踪

Kalman-Like Unbiased FIR Filter Improves Carrier Tracking Under High Dynamic Conditions

中文关键词:  卡尔曼  无偏FIR滤波器  高动态  载波跟踪环

英文关键词:Kalman  unbiased FIR filter  high dynamic  carrier tracking loop

中文摘要:

      针对传统锁频环(Frequency Locked Loop，FLL)辅助锁相环(Phase Locked Loop,PLL)在高动态环境下对卫星导航信号跟踪精度弱的问题，提出了利用类卡尔曼无偏有限长单位冲激响应（Finite Impulse Response,FIR）滤波器改进载波跟踪的方法。该方法无须已知系统状态噪声、测量噪声模型，基于经典卡尔曼载波跟踪模型，首次建立了类卡尔曼无偏FIR载波跟踪扩展模型。根据无偏估计原理，推导类卡尔曼无偏FIR滤波器增益矩阵，利用N点历史相位差数据和可程序化运行的递归算法实时计算三态估计矩阵。针对喷气推进实验室（Jet Propulsion Laboratory,JPL)高动态运动模型的仿真结果表明，相较于传统FLL+PLL载波跟踪方法，所提方法提高了载波相位、频率的跟踪精度，增强了跟踪环路的鲁棒性。载噪比为42 dB-Hz时，相位跟踪精度提升了97.8%，频率跟踪精度提升了54.6%，同时环路跟踪时间有所缩短。

英文摘要:

      A method for improving carrier tracking using Kalman-like unbiased finite impulse response(FIR) filter is proposed to address the issue of weak tracking accuracy of traditional frequency locked loop(FLL) assist phase locked loop(PLL) in high dynamic environments for satellite navigation signals.This method does not need to know the system state noise and measurement noise model.Based on the classical Kalman carrier tracking model,the Kalman-like unbiased finite impulse response(FIR) carrier tracking extended model is established for the first time.According to the principle of unbiased estimation,the Kalman-like unbiased FIR carrier tracking gain matrix is derived.By using N points historical phase difference data and programmable recursive algoritms,the three-state estimation matrix is calculated in real time.The simulation results for the jet propulsion laboratory(JPL) high dynamic motion model show that compared to the traditional FLL+PLL method,the proposed method improves the tracking accuracy of carrier phase and frequency,and enhances the robustness of the tracking loop.When the carrier to noise ratio is 42 dB-Hz,the phase tracking accuracy is improved by 97.8%,the frequency tracking accuracy is improved by 54.6%,and the loop tracking time is shortened.