Kalman filter algorithm based on singular value decomposition

An algorithm for the discrete time linear filtering problem is developed. The crucial component of this algorithm involves the computation of the singular value decomposition (SVD) of an unsymmetric matrix without explicitly forming its left factor, which has a high dimension. The algorithm has good numerical stability and can handle correlated measurement noise without any additional transformation. Since the algorithm is formulated in the form of vector-matrix and matrix-matrix operations, it is also useful for parallel computers. A numerical example is given