Improving the response of a wheel speed sensor by using frequency-domain adaptive filtering

Abstract

In this paper, a frequency-domain least-mean-square adaptive filter is used to cancel noise in a wheel speed sensor embedded in a car under performance tests. In this case the relevant signal is buried in a broad-band noise background, where we have little or no prior knowledge of the signal or noise characteristics. The results of the experiments show that the signal of interest and the noise (all forms of interference, deterministic, as well as stochastic) share the same frequency band and that the filter used significantly reduced the noise corrupting the information from the sensor while it left the true signal unchanged from a practical point of view. In this paper, a signal-to-noise ratio improvement higher than 40 dB is achieved. The results of the experiment show the importance of using digital signal processing when dealing with a signal corrupted by noise.