### Abstract

The Second Order Kalman Filter (SOKF) uses a second order Taylor series expansion (TSE) to account for nonlinearities in an estimation problem. In this work, the derivatives required for the SOKF are computed using multicomplex (MCX) derivatives, coded in the Matlab programming language. This method uses function overloading in order to derive or compute the derivatives to machine precision without having to compute the derivatives analytically. Thus, the SOKF can be easily implemented, while at the same time having fewer tuning parameters than other high order filters. The standard SOKF is also extended by combining it with Gaussian Mixture models (GMM), which gives promising results. The filters have been used to estimate the state of a 1 DOF falling body. The results show that the MCX computes the required derivatives just as accurately as an analytical method and the SOKF and GMM modification perform well in terms of accuracy compared to other filters. Despite the ease of use and high accuracy benefits, a current drawback of the MCX method is compute speed. Methods for improving the speed are beyond the current scope and will be addressed in future works.

Original language | English (US) |
---|---|

Title of host publication | Advances in the Astronautical Sciences |

Pages | 1517-1532 |

Number of pages | 16 |

Volume | 143 |

State | Published - 2012 |

Externally published | Yes |

Event | 22nd AAS/AIAA Space Flight Mechanics Meeting - Charleston, SC, United States Duration: Feb 2 2012 → Feb 2 2012 |

### Other

Other | 22nd AAS/AIAA Space Flight Mechanics Meeting |
---|---|

Country | United States |

City | Charleston, SC |

Period | 2/2/12 → 2/2/12 |

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### ASJC Scopus subject areas

- Aerospace Engineering
- Space and Planetary Science

### Cite this

*Advances in the Astronautical Sciences*(Vol. 143, pp. 1517-1532)

**Second-Order Kalman Filters using multi-complex step derivatives.** / Vittaldev, Vivek; Russell, Ryan P.; Arora, Nitin; Gaylor, David.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Advances in the Astronautical Sciences.*vol. 143, pp. 1517-1532, 22nd AAS/AIAA Space Flight Mechanics Meeting, Charleston, SC, United States, 2/2/12.

}

TY - GEN

T1 - Second-Order Kalman Filters using multi-complex step derivatives

AU - Vittaldev, Vivek

AU - Russell, Ryan P.

AU - Arora, Nitin

AU - Gaylor, David

PY - 2012

Y1 - 2012

N2 - The Second Order Kalman Filter (SOKF) uses a second order Taylor series expansion (TSE) to account for nonlinearities in an estimation problem. In this work, the derivatives required for the SOKF are computed using multicomplex (MCX) derivatives, coded in the Matlab programming language. This method uses function overloading in order to derive or compute the derivatives to machine precision without having to compute the derivatives analytically. Thus, the SOKF can be easily implemented, while at the same time having fewer tuning parameters than other high order filters. The standard SOKF is also extended by combining it with Gaussian Mixture models (GMM), which gives promising results. The filters have been used to estimate the state of a 1 DOF falling body. The results show that the MCX computes the required derivatives just as accurately as an analytical method and the SOKF and GMM modification perform well in terms of accuracy compared to other filters. Despite the ease of use and high accuracy benefits, a current drawback of the MCX method is compute speed. Methods for improving the speed are beyond the current scope and will be addressed in future works.

AB - The Second Order Kalman Filter (SOKF) uses a second order Taylor series expansion (TSE) to account for nonlinearities in an estimation problem. In this work, the derivatives required for the SOKF are computed using multicomplex (MCX) derivatives, coded in the Matlab programming language. This method uses function overloading in order to derive or compute the derivatives to machine precision without having to compute the derivatives analytically. Thus, the SOKF can be easily implemented, while at the same time having fewer tuning parameters than other high order filters. The standard SOKF is also extended by combining it with Gaussian Mixture models (GMM), which gives promising results. The filters have been used to estimate the state of a 1 DOF falling body. The results show that the MCX computes the required derivatives just as accurately as an analytical method and the SOKF and GMM modification perform well in terms of accuracy compared to other filters. Despite the ease of use and high accuracy benefits, a current drawback of the MCX method is compute speed. Methods for improving the speed are beyond the current scope and will be addressed in future works.

UR - http://www.scopus.com/inward/record.url?scp=84879330624&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84879330624&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84879330624

SN - 9780877035817

VL - 143

SP - 1517

EP - 1532

BT - Advances in the Astronautical Sciences

ER -