Wavelet denoising for a strapdown north finder

Ming Rong Ren*, Xing Qiao Liu, Jia Bin Chen, Chang Jiang Zhang, Ling Xie, Jian Hua Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

To improve the accuracy of a strapdown north finder used under dynamic conditions of disturbances, a wavelet denoising method is introduced to process the original output of the north finder. From wavelet transform modulus across scales, it is seen that the useful signal is stable and some maximum modules does not decrease in larger scales. So maximum modules and soft-thresholding are proposed. Some maximum modules whose values grow larger with increase in their scales are substituted by mean value of non-maximum modules adjacent to them. Thus disturbances whose Lipschitz exponent is larger than zero are filtered. Soft-thresholding is used to filter the noise whose Lipschitz exponent is smaller than zero. The method can improve the accuracy of strapdown finder to 1 mrad.

Original languageEnglish
Pages (from-to)592-595
Number of pages4
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume24
Issue number7
Publication statusPublished - Jul 2004

Keywords

  • Dynamic disturbance
  • Locale maximum modulus
  • Soft-thresholding
  • Strapdown north finder
  • Wavelet denoising

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