Paper Title:
Quantized Kalman Filter for Sensor Networks with Random Packet Dropouts
  Abstract

Based on the projection theory and the uniform quantization method, a quantized Kalman filter is presented for sensor networks with random packet dropouts from sensors to the fusion center (filter). The bandwidths are scheduled by the optimality index that energy consumption is minimized under a given performance constraint. Compared with the filter without quantization, the quantized filter given can reduce the energy consumption and has an effective tracking performance. A simulation example demonstrates the effectiveness of the proposed algorithm.

  Info
Periodical
Advanced Materials Research (Volumes 219-220)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
1040-1044
DOI
10.4028/www.scientific.net/AMR.219-220.1040
Citation
N. Liu, J. Ma, S. L. Sun, "Quantized Kalman Filter for Sensor Networks with Random Packet Dropouts", Advanced Materials Research, Vols. 219-220, pp. 1040-1044, 2011
Online since
March 2011
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$32.00
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