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Influence of measurement noise on the performance and convergence of the filtered-x LMS algorithm; Theory and simulations
Ansvarig organisation
2010 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat) Published
Abstract [en]

In active noise control (ANC) applications the sensor signals feeding the controller may be contaminated by signal components not linearly related to the actual noise to be controlled, e.g. measurement noise. An example is the noise in the microphone signals generated by airflow turbulence when applying ANC to ducts. The measurement noise may significantly degrade the performance of an ANC system. This paper is concerned with theoretical investigations of the influence of measurement noise on the performance and convergence of the filtered-x LMS algorithm. Further, computer simulations have been performed to verify the theoretical results. In the theoretical investigations, the convergence of the filtered-x LMS algorithm is derived for different cases with measurement noise affecting the different sensor signals. These cases are compared to the ideal case with no measurement noise present at neither sensor signal. The results from both the theoretical investigations and the simulations show that measurement noise can, depending on the SNR of the sensor signals, degrade the performance of the filtered-x LMS algorithm regarding both the filter coefficients the algorithm converges to in mean, and the convergence rate of the algorithm.

Ort, förlag, år, upplaga, sidor
Cairo: International Institute of Acoustic and Vibration , 2010.
Nyckelord [en]
Active Noise Control, Adaptive Signal Processing, Filtered-x LMS Algorithm, Measurement Noise
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:bth-7738Lokalt ID: oai:bth.se:forskinfo9B258C61F563369CC125778C0041CFFEOAI: oai:DiVA.org:bth-7738DiVA, id: diva2:835393
Konferens
ICSV17
Tillgänglig från: 2012-09-18 Skapad: 2010-08-27 Senast uppdaterad: 2015-06-30Bibliografiskt granskad

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Johansson, SvenClaesson, IngvarHåkansson, Lars

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