基于“当前”统计模型的自适应不敏卡尔曼滤波算法

Adaptive Unscented Kalman Filtering Algorithm Based on Current Statistical Model

基于机动目标"当前"统计模型在直角坐标系下建立了三坐标雷达跟踪系统的状态方程和观测方程。针对非线性自适应滤波这一问题,提出了一种基于"当前"统计模型的自适应不敏卡尔曼滤波算法(CS-UKF),并对算法作了说明。通过计算机仿真验证了CS-UKF算法的有效性,并且该算法跟踪效果良好,精度好于基于"当前"统计模型的自适应扩展卡尔曼滤波算法(CS-EKF)算法。

State equation and observation equation of three dimensional radar tracking system are built based on current statistical model. In order to solve the problem about nonlinear adaptive filtering, a novel algorithm is presented and explained. The validity of the new algorithm is proved by the simulated results and the results also indicate that CS-UKF whose tracking precision is better than CS-EKF can track target very well.