A new class of particle filters for random dynamic systems with unknown statistics
EURASIP Journal on Applied Signal Processing
Exploiting motion correlations in 3-D articulated human motion tracking
IEEE Transactions on Image Processing
A fixed-lag particle smoother for blind SISO equalization of time-varying channels
IEEE Transactions on Wireless Communications
Robust Kalman filter based on a generalized maximum-likelihood-type estimator
IEEE Transactions on Signal Processing
A Rao-Blackwellized particle filter for joint channel/symbol estimation in MC-DS-CDMA systems
IEEE Transactions on Communications
IEEE Transactions on Communications
Rao-blackwellised particle filtering for dynamic Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Marginalized particle filters for mixed linear/nonlinear state-space models
IEEE Transactions on Signal Processing
Particle filters for state estimation of jump Markov linear systems
IEEE Transactions on Signal Processing
Autoregressive modeling for fading channel simulation
IEEE Transactions on Wireless Communications
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This paper develops a state estimation method for conditionally linear dynamic systems in unknown non-Gaussian noises, which is a combination of the H"~ filter and the cost-reference particle filter (PF). The proposed method has similar algorithmic structure as the mixture Kalman filter (MKF), which is a combination of the Kalman filter and the standard PF for conditionally linear dynamic Gaussian systems. The MKF requires the knowledge of the noise distributions and the noises are Gaussian or conditional Gaussian with known parameters in the model, which might not hold in many practical applications, while the proposed method does not require the knowledge of the noise distributions and the noises can be non-Gaussian, so it is more flexible and has less limitation in applications. Two applications of the proposed method in telecommunications, as well as the computer simulation results, are provided to illustrate the performance of the proposed method.