中文摘要：

通常情况下使用Kalman滤波器进行参数估计，然而在目标运动模型和噪声统计特性存在不确定性的条件下，Kalman滤波的应用将会受到一些限制。在分析ESO滤波器滤波性能的基础上，将其应用在运动参数估计中，有效地解决Kalman滤波所遇到的问题．并从系统噪声分别为高斯白噪声、有色噪声和目标作机动运动这三个方面与Kalman滤波器进行了比较。仿真结果表明ESO滤波器算法简单，有效，具有鲁棒性。

英文摘要：

In general conditions, Kalman filter technique has been applied extensively in parameter estimation. When there is uncertainty in dynamic model or the statistics of noise sources are not fully known or unavailable, the application of Kalman filter is restricted. ESO filter was introduced and applied in motion parameter estimation, which ef[ectively solved the problems that appeared in the applications of Kalman filtering, Their performances were compared and studied when the observation noise was Gaussian white noise, color noise and moving object was maneuvering .The simulation results illustrate that ESO filter is simple, effective, and robust.