Detecting Moving Targets in Ground Clutter Using RBF Neural Network

  • Authors:

  • Jian Lao;Bo Ning;Xinchun Zhang;Jianye Zhao

  • Affiliations:

  • School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871;School of Electronics Engineering and Computer Science, Peking University, Beijing, China 100871

  • Venue:
  • ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
  • Year:
  • 2008

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Abstract

In this paper, a new structure for moving targets detection and characteristics extraction in ground clutter is proposed. This structure combines Radial Basis Function (RBF) neural network, Burg algorithm, and notch filter. After dynamical reconstruction, the RBF network is used to predict the ground clutter. Spectral characteristics of the ground clutter are estimated using the Burg algorithm. We apply notch filter to cancel the interference caused by the ground clutter. Moreover, a hardware platform based on FPGA is also realized for this paper to demonstrate this proposed structure and sufficient details of the hardware platform are discussed. The results of simulation and hardware implementation show that the presented structure has a good performance in processing target signals mixed with the ground clutter.