The invention provides an unmanned aerial vehicle formation collaborative navigation method based on an open
information fusion architecture, belongs to the field of unmanned aerial vehicle navigation, and aims to solve the navigation
information fusion problem of asynchronous updating of multi-sensor data and available dynamic change of measurement information in a traditional formation collaborative navigation method. In the prior art, when
asynchronous data fusion and measurement
information availability change are coped, the defects of precision loss, poor flexibility and expansibility and the like exist. According to the method, a
state variable and a measurement information set are constructed under an
open architecture, a
probability model of collaborative navigation state
estimation is established based on Bayesian reasoning, and on this basis, a
factor graph model is constructed by combining an incidence relation between a measurement model in
posterior probability and
prior information. By designing an independent measurement factor for each sensor, when sensor data is updated, flexible response to
asynchronous data fusion and dynamic change of measurement information is realized by optimizing changed measurement factor nodes in real time and dynamically adding and deleting the nodes. And gradually minimizing an error cost function of each factor node through a nonlinear least square optimization method to realize efficient fusion of multi-sensor data and real-time updating of a navigation state. According to the method, the efficiency, flexibility and expansibility of asynchronous
information fusion of the collaborative
navigation system are remarkably improved, and reliable
technical support is provided for unmanned aerial vehicle formation collaborative navigation.