Performance analysis of adaptive noise canceller in real-time automobile environments

摘要

In this paper, we proposed an algorithm for adaptive noise cancellation (ANC) using the variable step size least mean square (VSSLMS) in real-time automobile environment. As a basic algorithm for ANC, the LMS algorithm has been used for its simplicity. However, the LMS algorithm has problems of both convergence speed and estimation accuracy in real-time environment. In order to solve these problems, the VSSLMS algorithm for ANC is considered in a nonstationary environment. By computer simulation using real-time data acquisition system (USB 6009), the VSSLMS algorithm turns out to be more effective than the LMS algorithm in both convergence speed and estimation accuracy, especially for the colored input signal used in ANC of engine noise.