A conditional cubature Kalman filter and its application to transfer alignment of distributed position and orientation system

Aiming at the problems of the accuracy and real-time performance in transfer alignment of airborne distributed position and orientation system (POS), a conditional cubature Kalman filter (CCKF) is proposed. In this method, the state variables of the non-linear mathematical model for transfer alignment are divided into two groups firstly—one group are linear variables that are independent with nonlinear variables, while the other group is composed of nonlinear variables and the linear ones coupled with them. And then, sampling is conducted to the second group of variables to realize the propagation of the cubature points, and the first group of variables is updated by using the conditional distribution of high-dimensional Gaussian random variables at the same time, therefore, time update for all state variables is completed. In the end, measurement update is performed for all state variables. The simulations results show that the proposed method can effectively reduce the computation burden while ensure the accuracy of transfer alignment.