UDU卡尔曼滤波器的信息公式化。
Information Formulation of the UDU Kalman Filter.
作者信息
D'Souza Christopher, Zanetti Renato
机构信息
Aeroscience and Flight Mechanics Division, EG6, 2101 NASA Parkway, NASA Johnson Space Center, Houston, Texas 77058.
Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, Texas 78712.
出版信息
IEEE Trans Aerosp Electron Syst. 2019 Feb;55(1):493-498. doi: 10.1109/TAES.2018.2850379. Epub 2018 Jun 25.
A new information formulation of the Kalman filter is presented where the information matrix is parameterized as the product of an upper triangular matrix, a diagonal matrix, and the transpose of the triangular matrix (UDU factorization). The UDU factorization of the Kalman filter is known for its numerical stability, this work extends the technique to the information filter. A distinct characteristic of the new algorithm is that measurements can be processed as vectors, while the classic UDU factorization requires scalar measurement processing, i.e. a diagonal measurement noise covariance matrix.
提出了一种卡尔曼滤波器的新信息公式，其中信息矩阵被参数化为一个上三角矩阵、一个对角矩阵和该三角矩阵转置的乘积（UDU分解）。卡尔曼滤波器的UDU分解以其数值稳定性而闻名，这项工作将该技术扩展到了信息滤波器。新算法的一个显著特点是测量可以作为向量进行处理，而经典的UDU分解需要标量测量处理，即对角测量噪声协方差矩阵。
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