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Tracking filter engineering : the Gauss-Newton and polynomial filters /

Identifying an alternative approach to filter engineering and the traditional Kalman filters, this new book highlights the important advantages of the Gauss-Newton filters.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Morrison, Norman
Autor Corporativo: Institution of Engineering and Technology
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Institution of Engineering and Technology, ©2013.
Colección:IET radar, sonar, navigation and avionics series ; 23.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Preface; Acknowledgements; Why this book?; Organisation; Part 1. Background; 1. Readme_First; 2. Models, differential equations and transition matrices; 3. Observation schemes; 4. Random vectors and covariance matrices
  • theory; 5. Random vectors and covariance matrices in filter engineering; 6. Bias errors; 7. Three tests for ECM consistency; Part 2. Non-recursive filtering; 8. Minimum variance and the Gauss-Aitken filters; 9. Minimum variance and the Gauss-Newton filters; 10. The master control algorithms and goodness-of-fit; Part 3. Recursive filtering.
  • 11. The Kalman and Swerling filters12. Polynomial filtering
  • 1; 13. Polynomial filtering
  • 2; References; Index.