基于UKF的双平台无源融合跟踪方法

针对存在配准偏差的双平台无源融合跟踪系统,提出了基于扩维Unscented卡尔曼滤波的配准跟踪一体化方法,在跟踪算法中,采用模糊调度方法调节＂当前＂统计模型参数,引入渐消因子,能够在状态发生突变时,迅速调整系统参数,提高了系统的抗机动目标自适应能力。仿真结果表明,这种跟踪算法能够较好地解决双平台无源融合跟踪系统中的配准偏差问题。

Algorithm of Two-observer Passive Fusion Tracking Based on UKF

In a two-observer passive fusion tracking system,an unscented fuzzy-controlled "current" statistic model adaptive filter for Tracking Maneuvering Target was proposed. UKF was proposed to estimate target states and register these sensors simultaneously. Due to abrupt change in the state or system biases,fading factor was introduced to this algorithm to keep fast response. The proposed algorithm is robust in a wide range of maneuvers. Simulations show that the tracking algorithm addresses well the registration errors in the two-observer passive tracking system.