Optimising the algorithm design for high-integrity relative navigation using carrier-phase relative GPS integrated with INS.
Presented at: UNSPECIFIED.
An increasing number of applications require the provision of a relative navigation solution which exhibits both high accuracy and high integrity. Examples include air-to-air refuelling (AAR) of unmanned air vehicles (UAVs) and automated landing of aircraft on ships. In a previous paper, QinetiQ demonstrated that adding inertial navigation to a carrier-phase relative GPS system can improve performance in a number of respects. This paper proposes an optimised processing architecture for high-integrity carrier-phase relative INS/GPS. This comprises at least one "single node" navigation processor aboard each vehicle and a relative navigation processor aboard the roving vehicle. For protection against reference user equipment failure, a fusion algorithm may be used to combine information from multiple single-node navigation processors aboard the reference vehicle. A patent-pending technique has been developed to ensure that the double-differenced carrier phase ambiguities remain integer multiples of the wavelength. The options for how and whether to combine GPS measurements, what to estimate as Kalman filter states and how many satellites the integration algorithms should handle are discussed and preferences identified. The trade-off between a partitioned and a differenced architecture for the relative navigation algorithm is discussed. The use of parallel solution hypotheses for fault isolation and exclusion is described and the integrity monitoring architecture summarised. Lastly, further work is proposed to improve the integrity of ambiguity fixing and develop a hybrid analytical and simulation-based performance model for determining a lower bound to relative INS/GPS solution availability.
|Type:||Conference item (UNSPECIFIED)|
|Title:||Optimising the algorithm design for high-integrity relative navigation using carrier-phase relative GPS integrated with INS|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Civil, Environmental and Geomatic Engineering
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