Name
Abstract | ||
|---|---|---|
This letter deals with the Kalman filter (KF) based on a third-order integrated random walk model (RW3). The resulting filter, noted as RW3-KF, is well suited to track slow time-varying parameters with strong trend behaviour. We first prove that the RW3-KF in steady-state admits an equivalent structure to the third-order digital phase-locked loops (DPLL). The approximate asymptotic mean-squared-error (MSE) is obtained by solving the Riccati equations, which is given in a closed-form expression as a function of the RW3 model parameter: the state noise variance. Then, the closed-form expression of the optimum state noise variance is derived to minimize the asymptotic MSE. Simulation results are given for the particular case where the parameter to be estimated is a Rayleigh channel coefficient with Jakes' Doppler spectrum. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/LSP.2013.2277668 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
jakes doppler spectrum,steady-state performance,kalman filters,parameter estimation,third-order digital phase-locked loops,third-order kalman filter,slow time-varying parameter tracking,mse,dpll,riccati equations,rw3-kf,third-order integrated random walk model,kalman filter (kf),random walk model (rw),rayleigh channel coefficient,approximate asymptotic mean-squared-error,closed-form expression,optimum state noise variance,rayleigh channels,mean square error methods | Alpha beta filter,Mathematical optimization,Extended Kalman filter,Fast Kalman filter,Random walk,Kalman filter,Estimation theory,Ensemble Kalman filter,Invariant extended Kalman filter,Mathematics | Journal |
Volume | Issue | ISSN |
20 | 11 | 1070-9908 |
Citations | PageRank | References |
4 | 0.46 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huaqiang Shu | 1 | 12 | 2.78 |
| Eric Pierre Simon | 2 | 84 | 11.32 |
| Laurent Ros | 3 | 28 | 5.35 |