摘要
介绍一种自适应调整过程噪声方差的滤波计算新方法。此方法不需要目标机动的先验知识,而是构造一个可自适应调整的缩放因子,通过该因子对过程噪声进行调节。结合协方差匹配自适应滤波算法的思想,给出一种新的机动目标跟踪算法。通过蒙特卡洛仿真,同IMM算法进行比较,结果表明算法在目标发生机动时具有更好的性能。
A new filtering approach is proposed for calculating the variance of adaptive adjustment process noise. This approach does not rely on the prior knowledge to the target motion, and utilizes a zoom factor, which can adjust itself adaptively. By this factor, the process noise covariance can be modified . By using the idea of covariance matching, a new maneuvering target tracking algorithm is proposed. By means of Monte - Carlo simulation, the performance of the proposed algorithm is compared with that of an IMM algorithm. The proposed filter produces better estimates than the IMM algorithm during maneuvering periods.
出处
《电光与控制》
北大核心
2007年第2期8-11,共4页
Electronics Optics & Control
关键词
机动目标跟踪
自适应滤波
过程噪声
缩放因子
maneuvering target tracking
adaptive filtering
process noise
zoom factor
