Abstract: Disclosed is an online dynamic mutual-observation modeling method for unmanned aerial vehicle (UAV) swarm collaborative navigation, which includes: first performing first-level screening for members according to the number of usable satellites received by a satellite navigation receiver of each member, to determine the role of each member in collaborative navigation at the current time, and then establishing a moving coordinate system with each object member to be assisted as the origin, and calculating coordinates of each candidate reference node; and on this basis, performing second-level screening for the candidate reference nodes according to whether mutual distance measurement can be performed with each object member, to obtain a usable reference member set, and preliminarily establishing a dynamic mutual-observation model; and finally, optimizing the model by means of iterative correction, and conducting a new round of dynamic mutual-observation modeling according to an observation relationship in the U