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The astro-inertial integrated navigation system has the characteristic of anti-electromagnetic interference but suffers from aero-optical starlight perturbation when applied to hypersonic cruise vehicles (HCVs). Because there is no strategy in the traditional loosely coupled astro-inertial integration framework for recognising and evaluating skew in star observation, this system cannot adapt to perturbations, and the navigation accuracy tends to degrade. In this study, a strongly coupled framework for an astro-inertial integrated system is designed, and a robust astro-inertial fusion algorithm based on star-coordinate matching is proposed; the skew degree of each observed star is quantified by matching with the virtual star image re-established from INS measurements. Based on star-coordinate matching, a robust weight-tuning rule is designed according to the maximum-likelihood estimation theory, including a method to determine the star-coordinate confidence scope by statistically analysing the astronomical-observation perturbation rate. Compared with the traditional loosely coupled astro-inertial integration framework, the proposed strongly coupled framework and robust astro-inertial integrated navigation algorithm based on star-coordinate matching can significantly improve robustness against perturbations. [ABSTRACT FROM AUTHOR]

In ordinary aircrafts, the geographic coordinate is usually taken as reference coordinate to build navigation systems. Changes of gravity field and radius caused by the non-perfect sphere and uneven mass distribution of the earth are ignored or simplified in navigation algorithm, which have little effect on the accuracy of the navigation system in a short-time and short-distance flight. As the Aerospace Vehicles (ASVs) have to complete long-term on-orbit maneuver over wide flight enveloping, ignoring changes of gravity field and radius will bring about cumulative navigation errors and result in the declined accuracy of the navigation system. Hence, this paper first proposes an inertial navigation algorithm in launch inertial coordinate for ASVs aimed at reducing the effects caused by the inaccurate earth model on the navigation system. Then, the model of INS/CNS/GPS integrated navigation system in launch inertial coordinate is built. Considering the uncertain noise in space, the performance of Kalman filter may be poor, a robust filtering algorithm based on extended H ∞ filter is designed to realize multi-sensors information fusion; The state model and measurement model in launch inertial coordinate are built. The simulation results show that the proposed method and algorithm can improve the accuracy and reliability of the integrated navigation system for ASVs. [ABSTRACT FROM AUTHOR]

Aimed at the problem of nonlinear and time-varying noise characteristics in inertial and land-based integrated navigation system, a cubature Kalman filter algorithm based on maximum a posterior estimation and fading factor has been proposed, and the fuzzy control theory is used to make it better to track the time-varying noise characteristics. Nonlinear measurement model of the land-based navigation system has been established. Online identification and adaptive adjustment of the measurement noise features has been realized by means of the designed noise estimator, which can effectively improve the estimation precision and inhibit filtering divergence. The simulation results show that the method proposed by the paper has a higher filtering accuracy compared with the traditional cubature Kalman filter. The horizontal positioning accuracy is improved by about 40%, and the horizontal velocity accuracy is improved by about 60%. The new algorithm can enhance the applicability of the land-based navigation system in required navigation performance. [ABSTRACT FROM AUTHOR]