Spacecraft precision entry navigation using an adaptive sigma point Kalman filter bank

This work documents the development of a sigma point Kalman filter for the purpose of precision spacecraft navigation during the atmospheric entry, descent and landing phase. The use of the sigma point Kalman filter is driven by the desire to avoid complex partial derivatives associated with the standard extended Kalman filter. The strategy increases the likelihood that the navigation algorithm will be compatible with the Electra. Using Mars Exploration Rover Spirit (MER-A) and the Mars Science Laboratory (MSL) data, experiments were conducted to validate the proposed navigation concept. Beginning at atmospheric entry interface, the hypersonic entry phase is considered and the navigation architecture performance is quantified. Using the sigma point Kalman filter as the main computational unit, a filter bank for environmental parameter identification is investigated. The focus of the investigation is atmospheric parameter identification. The MERA mission is used to verify the ability of the filter bank to make appropriate selections. The navigation architecture is implemented on the Electra programmable radio, a flight hardware communication node available on spacecraft build for Mars exploration. The investigations show that the sigma point Kalman filter structure is very applicable to the atmospheric entry navigation problem. When used in conjunction with the filter bank concept, the overall navigation architecture is shown to be able to improve navigation accuracy over standard dead-reckoning, while providing robustness to uncertainties in the atmosphere. The navigation algorithm is successfully hosted on the Electra programmable radio and is capable of processing actual MER inertial measurement data.