Expectation maximization algorithm for GPS positioning in multipath environments based on Volterra series

Cites Work

Combined parameter and output estimation of dual-rate systems using an auxiliary model
Bias correction-based recursive estimation for dual-rate output-error systems with sampling noise
Volterra series and geometric control theory
Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs
Auxiliary variable-based identification algorithms for uncertain-input models
Optimal experiment design for identification of ARX models with constrained output in non-Gaussian noise
Application of adaptive filtering by selecting the parameter weight factor in precise kinematic GPS positioning
A novel reduced-order algorithm for rational models based on Arnoldi process and Krylov subspace
Some stochastic gradient algorithms for Hammerstein systems with piecewise linearity
Robust Kalman filtering for nonlinear multivariable stochastic systems in the presence of non-Gaussian noise
Identification and restoration of noisy blurred images using the expectation-maximization algorithm
Expectation-Maximization Gaussian-Mixture Approximate Message Passing
Identification of dual-rate systems based on finite impulse response models
Partially Coupled Stochastic Gradient Identification Methods for Non-Uniformly Sampled Systems
Parameter estimation of dual-rate stochastic systems by using an output error method
GPS positioning in a multipath environment
Interval Error Correction Auxiliary Model Based Gradient Iterative Algorithms for Multirate ARX Models
Fractional-based stochastic gradient algorithms for time-delayed ARX models
Recursive identification of errors-in-variables systems based on the correlation analysis

This page was built for publication: Expectation maximization algorithm for GPS positioning in multipath environments based on Volterra series

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6652354)