Generation of new exciting regressors for consistent on-line estimation for a scalar parameter

In this paper the problem of estimation of a single parameter from a linear regression equation in the absence of sufficient excitation in the regressor is addressed. A novel procedure to generate a new exciting regressor is proposed. The superior performance of a classical gradient estimator using this new regressor, instead of the original one, is illustrated with comprehensive simulations.