A consideration on blind estimation algorithm using total least squares based on over-sampling method

There is the over-sampling method which is one of the methods for realizing the blind estimation. In the conventional methods, The algorithms are proposed for the estimation system´s input signals not including noise. In the actual blind estimation, however, the estimation precisions of the conventional methods are lower because of the estimation system´s input signals include noise. To solve the problem, in the prior study, several persons in the members of our study propose the blind estimation algorithm using the total least squares (TLS) based on over-sampling method. In the prior study, it is used that the method which updates the filter coefficients by using the constant step gain and a simple gradient method. As the result, the estimation precision of the prior study is higher than those of the conventional methods. The prior study, however, has a problem that its convergence rate is slower. In this paper, and then, for developing the faster algorithm than the prior study, we considerate the algorithm which updates the filter coefficients by using the variable step gain and the updating method of the filter coefficients such as the recursive least squares (RLS), where it is the algorithm using TLS based on over-sampling method. As the result, it is clear that the proposed method has a faster convergence rate than the prior study, where these estimation precisions are about equal too, by computer simulation.