摘要
在科学和工程实践中，常常需要对动态系统的参数进行实时跟踪估计。传统卡尔曼滤波方法能够有效完成对线性系统的跟踪，而对非线性动态系统的跟踪性能较差。将粒子滤波器理论用于研究动态系统的跟踪问题，提出了基于粒子滤波器的参数跟踪方法。仿真实验表明，对于线性动态系统，该方法性能略优于广义卡尔曼滤波方法，而对于非线性动态系统，其参数跟踪性能则显著提高。
The problem of real-time tracking parameter of dynamic systems is a basic problem in science and engineering application, tranditional the Kalman filter is successfully applicated to linear systems. However it can＇t track the nonlinear systems effectively. In this paper, the particle filter theory is used to solve the tracking problem of dynamic systems, a general parameter tracking method is proposed based on particle filter. Simulation results demonstrate that the algorithm outperform the Extended Kalman Filter （EKF） method slightly for linear systems, while it performs much better than the EKF method for nonlinear systems,
