Particle Filter for Joint Carrier Phase, Doppler Shift and Doppler Rate Estimation and Data Detection

This paper proposes a novel method for joint estimation of carrier phase, Doppler shift, Doppler rate, and data detection using particle filter (PF). Using sequential importance sampling (SIS) the proposed algorithm estimates the posterior joint probability of unknown parameters and transmitted data symbols in a recursive fashion. We also propose a method for fine tuning of particles for quick convergence. The Monte Carlo simulations confirm the validity of the proposed algorithm. We show numerically that the bit error rate (BER) performance of the proposed particle filter with the fine tuning method is within 0.5-1 dB of the ideal scenario (no error in parameter estimation) with only 100 particles. Simulations with fine tuning of particles depict significant gains in signal-to-noise ratio (SNR) for root-mean-square error (RMSE) of Doppler shift and Doppler rate (compared to cases without fine tuning of particles).

Automated summary

This paper proposes a novel method for joint estimation of multiple parameters using particle filter and fine tuning of particles for faster convergence. Monte Carlo simulations confirm the validity of the proposed algorithm, showing that its performance is close to the ideal scenario in numerical terms.