Solution of ill-posed problem of optimal linear filtering with correlated noise (Q792285)

The mean-square optimal estimate of the state vector of an optimal linear filtering problem is usually obtained assuming that all the data are known exactly. In this paper the problem is taken from a more realistic situation often encountered in applications when, under suitable conditions, approximations are used. Here such an ill-posed optimal linear filtering problem is considered for the case of correlated input noise, and some methods for construction of stable algorithms are proposed.