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Volume 30 Issue 7
Jan.  2011
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Hou Dai-wen, Yin Fu-liang. Iterated Central Difference Kalman Filter Based Speaker Tracking[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1684-1689. doi: 10.3724/SP.J.1146.2006.01897
Citation: Hou Dai-wen, Yin Fu-liang. Iterated Central Difference Kalman Filter Based Speaker Tracking[J]. Journal of Electronics & Information Technology, 2008, 30(7): 1684-1689. doi: 10.3724/SP.J.1146.2006.01897

Iterated Central Difference Kalman Filter Based Speaker Tracking

doi: 10.3724/SP.J.1146.2006.01897
  • Received Date: 2006-11-30
  • Rev Recd Date: 2007-06-08
  • Publish Date: 2008-07-19
  • In the state space method based speaker tracking system, the nonlinearity of the measurement function degrades the localizing accuracy of the speaker tracking method severely. The iterated central difference Kalman filter algorithm, which incorporates the iterated filtering theory and the Central Difference Kalman Filter (CDKF) method, is proposed to reduce linearization error. In comparison with traditional CDKF method, the proposed method has higher tracking accuracy, faster convergence speed and more robust stability. Simulation results demonstrate the effectiveness of the proposed method.
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