Abstract:Aiming at the problems of asynchronous information fusion and multi-platform cooperative positioning when multi-UAV formation based on pure azimuth observation information for cooperative positioning and tracking the target, a linear pseudo-measurement model is proposed. The linear relationship between the target position and the measurement position is established through geometric derivation. Under the assumption of constant acceleration motion of the target, the data fusion of multi-platform asynchronous azimuth information is realized by using the Kalman filter, and the target motion state is accurately estimated. At the same time, a state update strategy based on event triggering is designed for the state estimator. To realize the state estimation of distributed computing, a global fusion method of asynchronous local state estimation results is designed according to the principle of covariance crossing. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments, and it is proved that the proposed asynchronous data state estimation method has better convergence speed and accuracy than the pseudo-synchronous extended Kalman filter method under the condition of continuous changes in target velocity.