Title
Networked strong tracking filters with noise correlations and bits quantization
Abstract
We study the design of quantized Kalman filters with strong tracking ability for the single sensor system with the correlation between process and measurement noises and adaptive bits quantization in this paper. Firstly, we perfect the problem formulation for the quantized tracking system about the correlation between original process and measurement noises and the correlation matrixes between quantized error and original process and measurement noises. Both are clear innovation in our study. Secondly, based on this problem formulation, two direct quantized Kalman filters are presented by use of statistical modeling and augmented state modeling ways respectively. Finally, the strong tracking method which can deal with noise correlation is used to propose two quantized strong tracking filters, which can effectively reduce the modeling uncertainty and get the strong tracking ability to the state abrupt change.
Year
DOI
Venue
2011
10.1007/978-3-642-23887-1_23
AICI (2)
Keywords
DocType
Volume
original process,direct quantized kalman filter,quantized kalman filter,measurement noise,strong tracking method,strong tracking ability,quantized tracking system,quantized error,noise correlation,bits quantization,problem formulation,networked strong tracking filter,quantized strong tracking filter
Conference
7003
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
6
2
Name
Order
Citations
PageRank
X. Xu112940.35
Quanbo Ge2287.31