  As the number of heterogeneous redundant sensors on unmanned aerial vehicle
(UAV) increases, onboard sensors require a more rational and efficient
credibility evaluation system and a resilient fusion framework to achieve the
essence of seamless sensor group switching. A simple and efficient sensor
credibility evaluation system is proposed to guide the selection of the optimal
multi-source sensor submodel combination, thereby providing key model prior
knowledge for multi-source resilient fusion. Furthermore, a multi-model
interactive resilient fusion framework based on RIEKF is proposed, utilizing
the defined sensor credibility indexes to guide the design of the model
transition probability matrix, thereby reducing the sensitivity of submodel
weights to fusion stability and solving the problem of the model transition
matrix lacking a basis for adjustment. Model weights are updated in real time
through credibility prior information and submodel posterior probabilities,
thus leveraging the adaptive resilience advantage between models to achieve
seamless switching between submodels in complex environments. Experimental
results show that the algorithm presented in this paper, without using any
sensor fault diagnosis and isolation logic, without setting any complex
detection timing and thresholds, demonstrates a resilience advantage, thereby
enhancing the adaptability of the state estimation system in complex
environments.
