Two-stage recursive least squares method for modeling power signals

This paper studies two-stage recursive least squares identification problems for power signals by the decomposition technique. The basic idea is to decompose a power signal model into two submodels and then to identify the parameters of each submodel, respectively. Compared with the recursive least squares algorithm, the dimensions of the involved covariance matrices in each submodel become small and thus the proposed algorithm has a high computational efficiency. Finally, the simulation results indicate that the proposed algorithm is effective.