Purpose The Embedded GPSINS System EGI has been used more widely as central navigation equipment of aircraft. For certain cases needing high attitude accuracy, star sensor can be integrated with EGI to improve attitude performance. Since the filteringcorrection loop has already built in finished EGI product, centralized or federated Kalman filter is not applicable for integrating EGI with star sensor it is a challenge to design multisensor information fusion algorithm suitable for this situation. The purpose of this paper is to present a doublelayer fusion scheme and algorithms to meet the practical need of constructing integrated multisensor navigation system by star sensor assisting finished EGI unit.Designmethodologyapproach The alternate fusion algorithms for asynchronous measurements and the sequential fusion algorithms for synchronous measurements are presented. By combining alternate filtering and sequential filtering algorithms, a kind of doublelayer fusion algorithms for multisensors is proposed and validated by semiphysical test in this paper.Findings The doublelayer fusion algorithms represent a filtering strategy for multiple nonidentical parallel sensors to assist INS, while the independent estimationcorrection loop in EGI is still maintained. It has significant benefits in updating original navigation system by integrating new sensors.Practical implications The approach described in this paper can be used in designing similar multisensor information fusion navigation system composed by EGI and various kinds of sensors, so as to improve the navigation performance.Originalityvalue Compared with conventional approach, in the situation that centralized and federated Kalman filter are not applicable, the doublelayer fusion scheme and algorithms give an external filtering strategy for measurements of finished EGI unit and star sensors.
Aircraft Engineering and Aerospace Technology – Emerald Publishing
Published: Jun 28, 2013
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