Kalman-Like Unbiased FIR Filter Improves Carrier Tracking Under High Dynamic Conditions
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)as-sist 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 es-tablished 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 re-cursive 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 meth-od,the proposed method improves the tracking accuracy of carrier phase and frequency,and enhances the robust-ness 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.
Kalmanunbiased FIR filterhigh dynamiccarrier tracking loop
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