一种精确跟踪机动目标的滤波算法的研究

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 nonlinear filtering algorithm for precise tracking of maneuvering target

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.