Volume 37 Issue 10
Oct.  2012
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LUO Zhicai, LIN Xu, ZHOU Boyang. Improved Algorithm of Autocovariance Least-Squares Noise Estimation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(10): 1164-1167.
Citation: LUO Zhicai, LIN Xu, ZHOU Boyang. Improved Algorithm of Autocovariance Least-Squares Noise Estimation[J]. Geomatics and Information Science of Wuhan University, 2012, 37(10): 1164-1167.
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Improved Algorithm of Autocovariance Least-Squares Noise Estimation

  • 1 School of Geodesy and Geomatics,Wuhan University,129 Luoyu Road,Wuhan 430079,China;2 Key Laboratory of Geospace Environment and Geodesy,Ministry of Education,Wuhan University, 129 Luoyu Road,Wuhan 430079,China;3 State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University, 129 Luoyu Road,Wuhan 430079,China

Funds: 国家自然科学基金资助项目(41174062,41131067);;中央高校基本科研业务费专项资金资助项目(2012214020206)
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  • Received Date: August 21, 2011
  • Published Date: October 04, 2012
    Graphical Abstract
    • Abstract
  • Noise estimation is the foundation for the application of Kalman filtering theory.The noise estimation results from the conventional autocovariance least-squares(ALS) are usually non-positive definite.For this purpose,an improved algorithm of ALS(IALS) is proposed to overcome effectively the problems of insufficient data and inaccurate priori information,and consequently to get positive definite noise estimates with better accuracy.Numerical simulation results validate the correctness of IALS.
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