多级火箭主动段跟踪主要采用基于当前统计模型的解耦卡尔曼滤波方法,当前统计模型的机动参数不能自适应变化时,在级间分离段会出现滤波突跳问题。针对于此,文中提出模型参数自适应计算方法,同时,采用容积卡尔曼滤波方法替换传统的解耦卡尔曼滤波方法。通过对某次火箭飞行实测数据分析,该算法能有效抑制滤波突跳问题,算法的稳定性及收敛性与传统方案相比有较为明显的改善,适用于多级火箭主动段跟踪。

Multistage rocket boost phase tracking mainly adopted decoupling Kalman filtering method based on current statistical model, when the maneuvering parameters of the current statistical model could not be adaptive to changes, separating section would take on filter kicking. To solve this problem, an adaptive calculation of model parameters was put forward and the cubature Kalman filter was used to solve nonlinear filtering problem. Through the analysis of measured data of a certain rocket flight, the algorithm could effectively restrain filter kicking, and the stability and convergence of the algorithm were obviously better than traditional scheme, and it was suitable for multistage rocket boost phase tracking.