Title
Comparison of quantized state estimators with different transmitted information forms
Abstract
Bandwidth limitation is an unavoidable constraint when data is transmitted from local sensor to the estimation center in networked systems. As a result, quantization strategy is often used to deal with this constraint during the design of networked state estimators. In this paper, we compare the performance of three quantized estimators with different transmitted data forms, such as the original measurement, the innovation and the local estimation. Firstly, adaptive bit quantization is introduced to deal with the bandwidth limitation constraint. Secondly, three quantized state estimators are introduced. Actually, they adopt the same quantizing strategy. Intervals and common variance upper approximation method are also used. Thirdly, we compare estimation accuracies of the three quantized estimators by using their estimation error co-variances. Finally, a simple simulation is demonstrated to validate the conclusion in our comparison. The results show that these three quantized filters have very similar estimation accuracy.
Year
DOI
Venue
2012
10.1109/ICMLC.2012.6359552
ICMLC
Keywords
Field
DocType
estimation,kalman filter,networked system,unavoidable constraint,common variance upper approximation method,state estimation,quantized filters,performance comparison,quantisation (signal),quantized estimators,networked state estimators,local sensor,information forms,adaptive bit quantization,networked systems,bandwidth limitation constraint,quantization strategy,quantized state estimators,estimation center,estimation error co-variances
Mathematical optimization,Bandwidth limitation,Pattern recognition,Computer science,Algorithm,Quantization (physics),Artificial intelligence,Upper approximation,Quantization (signal processing),Estimator
Conference
Volume
ISSN
ISBN
4
2160-133X
978-1-4673-1484-8
Citations 
PageRank 
References 
0
0.34
2
Authors
4
Name
Order
Citations
PageRank
X. Xu112940.35
Xianfeng Tang241.46
Bing-Lei Guan300.68
Quanbo Ge4287.31