提出了应用近似非线性滤波技术，辨识陀螺漂移误差模型的方法。
This paper presents the application of an approximate nonlinear filter in the identification of gyro drift error model.
扩展的卡尔曼滤波定位方法是一个常用的位置跟踪方法，但是在对非线性系统方程进行线性化近似过程中引入了线性化误差。
Extended Kalman Filter is an efficient tool for mobile robot position tracking, but it suffers from linearization errors due to linear approximation of nonlinear system equations.
由于扩展卡尔曼滤波必须假定噪声服从高斯分布，若用于复杂非线性系统，其估计精度不甚理想。粒子滤波对噪声类型没有限制，正在成为非线性系统状态估计的有效近似方法。
Because EKF must assume that the noise is subject to Gaussian distribution, the estimate accuracy is not so good if it is used to estimate the state of complicated nonlinear system.
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