针对强跟踪滤波算法对系统时变噪声缺乏自适应能力,导致系统状态估计精度较低的问题,提出一种可以在线估计噪声协方差阵的快速抑噪自适应强跟踪滤波算法,该算法可以抑制噪声对系统状态估计的影响,使系统状态估计迅速收敛到真实值附近.仿真实验对比了强跟踪滤波算法和快速抑噪自适应强跟踪滤波算法在噪声变化环境下的性能,结果表明:快速抑噪自适应强跟踪滤波算法具有更高的状态估计精度和自适应性. Aiming at the lack of self-adaptive ability of strong tracking filter to system time-varying noise and the low precision of system state estimation, a fast noise suppression adaptive strong tracking filter algorithm can be proposed to estimate noise covariance matrix on-line. This algorithm can suppress The influence of noise on the system state estimation makes the system state estimate converge rapidly to the real value.The simulation results show that the performance of the strong tracking filter algorithm and the fast noise suppression adaptive strong tracking filter algorithm in noisy environments show that the fast Noise adaptive strong tracking filter algorithm has higher state estimation accuracy and adaptability.