An Iterative Parameter Estimation Method for Observation Models with Nonlinear Constraints
An Iterative Parameter Estimation Method for Observation Models with Nonlinear Constraints
复制标题
非线性约束观测模型的迭代参数估计方法
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
T. Dang
中科院分区：
文献类型：
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作者：
T. Dang
本文提出了一种非线性约束观测模型的参数估计算法。属于这一类别的一个突出的例子是立体相机的连续自动校准。在这里，我们的知识之间的关系可用的测量和所需的参数是由一个非线性隐式约束方程。一个估计方法来自迭代扩展卡尔曼滤波器的设计，用于此应用程序。实验进行了合成和真实的数据。所提出的算法提供了非常好的结果，并很容易适用于更广泛的应用。
This article presents a parameter estimation algorithm for observation models with nonlinear constraints. A prominent example that belongs to this category is the continuous auto-calibration of stereo cameras. Here, our knowledge of the relation between the available measurements and the desired parameters is given by a nonlinear implicit constraint equation. An estimation method derived from an Iterated Extended Kalman Filter is designed for this application. Experiments are conducted with synthetic and real data. The proposed algorithm provides very good results and is readily applicable to a wider range of applications.