Study on the weak signal detection in the laser radar based on the chaos theory

Qing Wei Ping*, Gui Fen Xia

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper, we present a new method for the weak signal detection in the laser radar, which is based on that the laser echo is characteristic with chaos. The method is naturally rooted in nonlinear dynamical systems and relies on neural networks for its implementation. At first, this paper used the observed data to analyze the chaotic characteristics of the laser radar backscatter by calculating the chaotic character parameters, including correlation dimension, Lyapunov exponent and local predictability. Then the predictor model based on BP neural network is proposed. Experiment results show that the BP neural network predictor is a better math model. It is valuable for signal detection in chaotic series.

Original languageEnglish
Title of host publicationInternational Symposium on Photoelectronic Detection and Imaging 2007 - Laser, Ultraviolet, and Terahertz Technology
DOIs
Publication statusPublished - 2008
EventInternational Symposium on Photoelectronic Detection and Imaging 2007 - Laser, Ultraviolet, and Terahertz Technology - Beijing, China
Duration: 9 Sept 200712 Sept 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6622
ISSN (Print)0277-786X

Conference

ConferenceInternational Symposium on Photoelectronic Detection and Imaging 2007 - Laser, Ultraviolet, and Terahertz Technology
Country/TerritoryChina
CityBeijing
Period9/09/0712/09/07

Keywords

  • Chaos
  • Laser radar
  • Neural network
  • Prediction error
  • Signal detection

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