Identification techniques for correlated noise systems with multisensors

This paper presents system parameter estimators far correlated noise systems with multisensors. The system is described by a stochastic difference equation, while the integrated values of the output are observed by different sensors at discrete times. The so-called extended template function estimator is developed on the basis of the conjugate equation theory. Under some week conditions the parameter estimates obtained by the proposed method are asymptotically Gaussian distributed. It will be shown in this paper that the covariance matrix of this distribution can be optimized with respect to the vector of template functions and that an optimal vector of template functions really does exist. With the optimal choice of the template function vector the proposed estimator will give the same accuracy as the optimal instrumental variable estimator. When implementing the optimal template function method, a multistep algorithm consisting of four simple steps is proposed to estimate the system parameters and the parameters describing the noise characteristics