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Proceedings Paper

A BP neural network model for sea state recognition using laser altimeter
Author(s): Chun-bo Shi; Xiao-dong Jia; Sheng Li; Zhen Wang
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Paper Abstract

A BP neural network method for the recognition of sea state in laser altimeter is presented in this paper. Sea wave is the typical stochastic disturbance factor of laser altimeter effecting on low-altitude defense penetration of the intelligent antiship missiles, the recognition of sea state is studied in order to satisfy the practical needs of flying over the ocean. The BP neural network fed with the feature vector of laser range-measurement presents the analysis of features and outputs the estimation result of sea state. The two most distinguishing features are the mean and the variance of the sea echo, which are extracted from the distance characteristics of sea echo using general theory of statistics. The use of a feedforward network trained with the back-propagation algorithm is also investigated. The BP neural network is trained using sample data set to the neural network, and then the BP neural network trained is tested to recognize the sea state waiting for the classification. The network output shows the recognition accuracy of the model can up to 88%, and the results of tests show that the BP neural network model for the recognition of sea state is feasible and effective.

Paper Details

Date Published: 28 August 2009
PDF: 7 pages
Proc. SPIE 7382, International Symposium on Photoelectronic Detection and Imaging 2009: Laser Sensing and Imaging, 738251 (28 August 2009); doi: 10.1117/12.836356
Show Author Affiliations
Chun-bo Shi, Tianjin Jinhang Institute of Technical Physics (China)
Xiao-dong Jia, Tianjin Jinhang Institute of Technical Physics (China)
Sheng Li, Tianjin Jinhang Institute of Technical Physics (China)
Zhen Wang, Military Transportation Academy (China)


Published in SPIE Proceedings Vol. 7382:
International Symposium on Photoelectronic Detection and Imaging 2009: Laser Sensing and Imaging
Farzin Amzajerdian; Chun-qing Gao; Tian-yu Xie, Editor(s)

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