A parallel filtering algorithm for linear systems with unknown time varying noise statistics
| Autor: | D. Alspach |
|---|---|
| Rok vydání: | 1974 |
| Předmět: |
Kalman filter
Linear-quadratic-Gaussian control Invariant extended Kalman filter Computer Science Applications symbols.namesake Extended Kalman filter Additive white Gaussian noise Control and Systems Engineering Gaussian noise Control theory symbols Median filter Fast Kalman filter Electrical and Electronic Engineering Algorithm Mathematics |
| Zdroj: | IEEE Transactions on Automatic Control. 19:552-556 |
| ISSN: | 0018-9286 |
| DOI: | 10.1109/tac.1974.1100645 |
| Popis: | The problem of estimating the state of a linear dynamic system driven by additive Gaussian noise with unknown time varying statistics is considered. Estimates of the state of the system are obtained which are based on all past observations of the system. These observations are linear functions of the state contaminated by additive white Gaussian noise. A previously developed algorithm designed for use in the case of stationary noise is modified to allow estimation of an unknown Kalman gain and thus the system state in the presence of unknown time varying noise statistics. The algorithm is inherently parallel in nature and if implemented in a computer with parallel processing capability should only be slightly slower than the stationary Kalman filtering algorithm with known noise statistics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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