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Dynamic Compensating of Sensor Based on Noise Variance Estimation and Kalman Filtering(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2011年03期
Page:
13-17
Research Field:
Publishing date:

Info

Title:
Dynamic Compensating of Sensor Based on Noise Variance Estimation and Kalman Filtering
Author(s):
Cheng Zhanping
School of Computer Science and Technology,Nanjing Normal University,Nanjing 210046,China
Keywords:
dynamic compensation; noise; variance estimation; filtering
PACS:
TP212
DOI:
-
Abstract:
After sensor dynamic compensation，the output signal of the noise is increased and the variance is unknown． In order to effectively suppress noise，a dynamic compensation algorithm of adopting Kalman filter de-noising is researched in unknown measurement noise variance． Parameters of the compensator were obtained by reference model and system identification． At the same time，Kalman filter was constructed with reference mode to eliminate high frequency effected measurement precision． On account of the compensator’s output signal piecewise approximated by a polynomial with a degree of M，the noise variance can be estimated to utilize vanishing moments of wavelet，and the Kalman filter under the unknown measurement noise variance condition is valid． Simulation experimental results show that the approach is effective．

References:

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Memo

Memo:
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Last Update: 2013-03-21