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Abstract

A system and method for suppressing cyclic noise components of a sampled sensor signal generates an error compensation signal that is subtracted from the sampled sensor signal to produce a corrected signal. A moving average of the sampled sensor signal, or sensor error signal, is obtained that corresponds to an error signal free of the non-cyclic component. An adaptive noise compensation algorithm is implemented by a compensation module with a minimum number of multiplications. The compensation module relies upon a unit base vector having a length equal to the number of base functions used to represent the cyclic noise component of the sensor signal, or equal to the number of samples over the sampling interval of the cyclic noise. This base vector is multiplied by an adaptive gain, which is a function of the difference between the sensor error signal and a compensation signal output from the adaptive compensation module. A convergence gain module outputs a high gain or a low gain value that is multiplied by unit base vector to control the rate of convergence of the adaptive algorithm. An adaptive vector is the product of this multiplication, then passed through a one sampling period delay operator, and then combined as an inner product with the unit base vector to produce the adaptive compensation signal.

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