Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers
| dc.contributor.author | Jakubov, Ondrej | |
| dc.contributor.author | Kovar, Pavel | |
| dc.contributor.author | Kacmarik, Petr | |
| dc.contributor.author | Vejrazka, Frantisek | |
| dc.coverage.issue | 3 | cs |
| dc.coverage.volume | 22 | cs |
| dc.date.accessioned | 2015-01-21T11:47:02Z | |
| dc.date.available | 2015-01-21T11:47:02Z | |
| dc.date.issued | 2013-09 | cs |
| dc.description.abstract | Common techniques for position-velocity-time estimation in satellite navigation, iterative least squares and the extended Kalman filter, involve matrix operations. The matrix inversion and inclusion of a matrix library pose requirements on a computational power and operating platform of the navigation processor. In this paper, we introduce a novel distributed algorithm suitable for implementation in simple parallel processing units each for a tracked satellite. Such a unit performs only scalar sum, subtraction, multiplication, and division. The algorithm can be efficiently implemented in hardware logic. Given the fast position-velocity-time estimator, frequent estimates can foster dynamic performance of a vector tracking receiver. The algorithm has been designed from a factor graph representing the extended Kalman filter by splitting vector nodes into scalar ones resulting in a cyclic graph with few iterations needed. Monte Carlo simulations have been conducted to investigate convergence and accuracy. Simulation case studies for a vector tracking architecture and experimental measurements with a real-time software receiver developed at CTU in Prague were conducted. The algorithm offers compromises in stability, accuracy, and complexity depending on the number of iterations. In scenarios with a large number of tracked satellites, it can outperform the traditional methods at low complexity. | en |
| dc.format | text | cs |
| dc.format.extent | 776-790 | cs |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Radioengineering. 2013, vol. 22, č. 3, s. 776-790. issn 1210-2512 | cs |
| dc.identifier.issn | 1210-2512 | |
| dc.identifier.uri | http://hdl.handle.net/11012/36928 | |
| dc.language.iso | en | cs |
| dc.publisher | Společnost pro radioelektronické inženýrství | cs |
| dc.relation.ispartof | Radioengineering | cs |
| dc.relation.uri | http://www.radioeng.cz/fulltexts/2013/13_03_0776_0790.pdf | cs |
| dc.rights | Creative Commons Attribution 3.0 Unported License | en |
| dc.rights.access | openAccess | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/ | en |
| dc.subject | Factor graph | en |
| dc.subject | GNSS | en |
| dc.subject | Kalman filter | en |
| dc.subject | PVT | en |
| dc.subject | sum-product algorithm | en |
| dc.title | Distributed Extended Kalman Filter for Position, Velocity, Time, Estimation in Satellite Navigation Receivers | en |
| dc.type.driver | article | en |
| dc.type.status | Peer-reviewed | en |
| dc.type.version | publishedVersion | en |
| eprints.affiliatedInstitution.faculty | Fakulta eletrotechniky a komunikačních technologií | cs |