Application of improved Kalman filter algorithm for the signal processing of electronic nose
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Abstract:
To reduce the noise signal in the sampled data of the Electronic nose(enose), an improved adaptive method based on Kalman filtering algorithm is presented, which can adaptively adjust measurement error variance, while denoise the NonGaussian noise in an enose output. A Kalman filtering model for measurement data processing is introduced based on the signal characteristics in the enose measurement processing. The improved adaptive filtering method is discussed in detail and applied to enose signal processing. The results demonstrate that the proposed method can adaptively reduce the noise signal in the enose measurement data processing and improve the sensitivity of enose measurement.
