Abstract: This paper presents an recursive algorithm for linearized Multi-Input-Multi -Output system parameters identification in measurement noise. Generally, recursive parameter identification methods either have to standarize the model of the objects or have to calculate many times for inversing the matrics, not only taking a lot of operational time but also tending to diverge when the inverse of the matrix does not exist. This method decomposesthe Multi-Input-Multi-Output linearized system parameters identification into a number of Multi-Input-Single-Output system parameter identifications, anP then to inverse the matrix becomes a number of times of invering the scalar quantity. That will be able to avoid divergency. And the method directly estimates parameters without standarizing the model, so that saves the operational time in practice. In the end, the method is checked with flight test data in measurement noise.

Key words: parameter identification, recursive estimation, Multi-Input-Multi-Output system