Gauss Newton variable forgetting factor recursive least squares for time varying parameter tracking

The Gauss-Newton variable forgetting factor recursive least squares (GN-VFF-RLS) algorithm is presented, which can be used to improve the tracking capability in time varying parameter estimation. Compared to the existing algorithm, the exponentially windowed recursive least squares (EW-RLS) algorithm with optimal forgetting factor, the presented method leads to a significant improvement in fast time varying parameter estimation. The effects of signal to noise ratio and nonstationarity have been tested using computer simulations with the given parameter model. An assessment of the performance of each algorithm is presented in terms of the mean-square-deviation (MSD).