Hardware implementation of an Adaptive Noise canceller in an automobile environment

Abstract

In this paper, we have researched the performance of an algorithm for an adaptive noise canceller (ANC) using the instantaneous signal to noise ratio variable step size algorithm (I-SNRVSS) in a real-time automobile environment. As a basic algorithm for ANC, the Least Mean Square (LMS) algorithm has been used for its simplicity. However, the LMS algorithm has problems of both convergence speed and estimation accuracy in a real-time environment. In order to solve these problems, many variable step size algorithms for ANC were applied in a nonstationary environment. This paper measures and investigates the performance of an adaptive noise canceller with a DSP processor (TI TMS320C6713) using the LMS algorithm and I-SNRVSS algorithm in an automobile environment. The I-SNRVSS algorithm turns out to be more effective than the LMS algorithm in both convergence speed and estimation accuracy for an ANC, especially for a colored input signal such as engine noise.