Application of Simplified Cubature Kalman Filter in Fire Control Attack by Airbome Infrared Search and Track System Independently

Supporting fire control attack independently is one of the most important operational requirements for the infrared search and track system in new generation fighter. This paper aims at the problems existing in the traditional nonlinear filtering methods of infrared search and track system, such as the rounding error introduced by the EKF method after locally linearizing the nonlinear system model, which causes the filtering accuracy poor, and the non-positive definiteness of the UKF method, caused by the improper setting of the weighting value of the sigma points, and so on. Here, the cubature kalman filter (CKF) method is introduced, and according to the characteristic that the target motion model of bearing-only tracking in infrared search and track system usually consists of linear state equation and nonlinear observation equation, a simplified expression in one-step prediction for both state estimation and its error covariance estimation is derived in the time update link, which avoids the complexity of the original algorithm in cubature points generation and related calculation. Finally, simulation experiment of independent fire control attack by infrared search and track system is made for the proposed method. The results show that compared with CKF method, simplified CKF method can significantly reduce the computational complexity. Compared with the UKF method, the convergence accuracy can be improved on the basis of improving the filter stability.