Variable-step self-adaptive filtering algorithm applied to active sonar self-interference suppression

Abstract

In order to reduce the conflict between the higher rate of convergence of the self-adaptive filtering algorithm and the lower misalignment rate, a variable step normalized self-adaptive filtering algorithm is proposed and applied to the active sonar emission leakage self-interference suppression system. This algorithm gets the expression of the optimal iterative variable step based on that the least mean square error exists between the optimal weight vector and the estimated value is the and then eliminates the impact of inputting noise estimation bias on the algorithm. And at last, we put the power of estimative residual SI signal into the expression of the optimal iterative variable-step and get the updated weight vector formula of the variable step normalized self-adaptive filtering algorithm. The filters can use different step length self-adaptively in different updated status. The results of the simulation experiments show that, compared to the traditional algorithm of the normalized minimum mean square error, the proposed algorithm has a lower average steady-state misalignment rate.