A new approach for filtering nonlinear systems
A new approach for filtering nonlinear systems
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DOI：
10.1109/acc.1995.529783
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发表时间：
1995-06
期刊：
影响因子：
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通讯作者：
S. Julier;J. Uhlmann;H. Durrant-Whyte
中科院分区：
文献类型：
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作者：
S. Julier;J. Uhlmann;H. Durrant-Whyte
本文对具有非线性过程和观测模型的滤波系统提出了一种新的递推线性估计器。该方法使用一种新的参数化的平均值和协方差，可以直接转换的系统方程，给出预测的转换后的平均值和协方差。我们表明，这种技术是更准确，更容易实现比扩展卡尔曼滤波器。具体来说，我们提出了经验的结果，新的过滤器的高度非线性运动学机动车辆的应用。
In this paper we describe a new recursive linear estimator for filtering systems with nonlinear process and observation models. This method uses a new parameterisation of the mean and covariance which can be transformed directly by the system equations to give predictions of the transformed mean and covariance. We show that this technique is more accurate and far easier to implement than an extended Kalman filter. Specifically, we present empirical results for the application of the new filter to the highly nonlinear kinematics of maneuvering vehicles.