Suppression of Engine Noise Harmonics Using Cascaded LMS Filters

Abstract:
The background noise recorded by microphones in a car environment is mainly caused by the engine, airflow and the tires. The engine noise can be suppressed by adaptive filtering if an engine speed reference is available. This reference information is usually available from the data stream of the vehicle bus. This work presents a new filter structure for the suppression of engine harmonics. The filter structure consists of cascaded time-domain least mean squares (LMS) filters. Known LMS filter structures use a common error signal to update the filter weights for all harmonics. However, the power of the engine noise is typically dominated by the low order harmonics. Therefore, we propose a filter structure where the engine noise harmonics are processed in succession. Cascading the LMS filters improves the filter adaptation of the higher order harmonics.