On comparison of online secondary path modeling methods with auxiliary noise

In the past few years, many methods were proposed to model the so-called secondary path on line for an active noise control (ANC) system. In these methods, an auxiliary noise is employed to excite the modeling process. Among many factors to affect the performance of these methods, some play important roles. They are: 1) power of auxiliary noise; 2) ability to detect secondary path change; 3) optimal step sizes for adaptive filters used in an ANC system and 4) independence between ANC and secondary path modeling processes. In literature, however, there is lack of analysis to show how these factors affect the performance of the ANC system. Moreover, the aforementioned online secondary path modeling methods have not been systematically evaluated. In this paper, the performance of these methods is evaluated by investigating the above-mentioned factors through both statistical analysis and computer simulations.