Skip to main content
SpringerLink
Log in

Combinatorial fractal Brownian motion model

  • Published:
Science in China Series E: Technological Sciences Aims and scope Submit manuscript

Abstract

To solve the problem of how to determine the non-scaled interval when processing radar clutter using fractal Brownian motion (FBM) model, a concept of combinatorial FBM model is presented. Since the earth (or sea) surface varies diversely with space, a radar clutter contains several fractal structures, which coexist on all scales. Taking the combination of two FBMs into account, via theoretical derivation we establish a combinatorial FBM model and present a method to estimate its fractal parameters. The correctness of the model and the method is proved by simulation experiments and computation of practial data. Furthermore, we obtain the relationship between fractal parameters when processing combinatorial model with a single FBM model. Meanwhile, by theoretical analysis it is concluded that when combinatorial model is observed on different scales, one of the fractal structures is more obvious.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Maragos, R., Sun Fang-Kuo, Measuring the fractal dimension of signals: Morphological covers and iterative optimization, IEEE, Trans. on SP, 1993 (1): 108.

    Article  Google Scholar 

  2. Naokazu Yokoya, Fractal-based analysis and interpolation of 3D natural surface shapes and their applications to their modeling, Computer Vision, Graphics and Image Processing, 1989, (46): 1.

    Article  Google Scholar 

  3. Crustzberg, R., Ivauov, E., Computing fractal dimension of image segments, Proc. III. Conf. on Computer Analysis and of Image and Patterns, CAIP’89, 1989, 110–116.

  4. Xie Wenlu, Xie Weixin, Fractal analysis and parameter extracting in time series, Signal Processing (in Chinese), 1997, (2): 97.

    Google Scholar 

  5. Gao Xiang, Lu Jieren, Chen Xiangdong, Fractal Brownian motion model in ship radiated noise, Sonic Proceeding, 1999, (1): 19.

    Google Scholar 

  6. Wang Zhengming, Yi Donyun, Modeling of Measured Data and Parameter Estimate, Changsha: Press of National University of Defense Technology, 1996.

    Google Scholar 

  7. Wang Zhengming, Zhu Jubo, Reduced parameter model on trajectory tracking data with applications, Science in China, Series E, 1999, 42(2): 190.

    Article  MATH  MathSciNet  Google Scholar 

  8. Oppenheim, A. V., Sheff, R. W., Digital Signal Processing, Beijing: Science Press, 1980, 293–334.

    Google Scholar 

  9. Haykin, S., Li Xiao Bo, Detection of signals in chaos, Proceedings of the IEEE, 1995, (1): 95.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National University of Defense Technology, 410073, Changsha, China

    Jubo Zhu & Diannong Liang

Authors
  1. Jubo Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diannong Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jubo Zhu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhu, J., Liang, D. Combinatorial fractal Brownian motion model. Sci. China Ser. E-Technol. Sci. 43, 254–262 (2000). https://doi.org/10.1007/BF02916829

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02916829

Keywords

Search

Navigation