A new approach to Kalman filtering for descriptor systems
Guosheng Zhang · Journal of Natural Science of Heilongjiang University · 2006
Based on matrix theory and Kalman filtering theory in the time domain, linear discrete-time descriptor stochastic systems were studied. Using Jordan decomposition for matrixes, descriptor systems can be changed into normal systems. An optimal descriptor Kalman filter is given by using normal systems’ result. It is a simple and recursive algorithm. It avoids the calculation of ARMA innovation model and white noise estimators. It is suitable for real time applications. A simulation example shows its effectiveness.