摘要
为真实反映目标机动范围与强度的变化,引入了机动目标的"当前"统计模型,提出了一种基于该模型的自适应卡尔曼滤波算法.仿真结果表明,能有效改善在机动目标跟踪中传统的卡尔曼滤波可能出现的发散情况,提高了跟踪的准确性和稳定性.
Current statistical model of maneuvering target track is presented to reflect the changes of intensity and scope of maneuvering target, and the adaptive Kalman filtering algorithm based on the current statistical model is built. Compared with traditional Kalman filtering, the simulation results indicate that the algorithm can correct the distribution problem, and improve the accuracy and stability of target track.
出处
《战术导弹技术》
2009年第1期79-81,16,共4页
Tactical Missile Technology
关键词
自适应卡尔曼滤波算法
统计模型
目标跟踪
adaptive Kalman filtering algorithm
statistical model
target track
