DOI QR코드

DOI QR Code

A Study on the Target Precision Intercept Algorithm based on the Target Size Estimation at CCD Image Sequence

표적 크기추정 기술 기반의 CCD 영상 표적 정밀 요격 성능 개선 연구

  • Jung, Yun Sik (Daegu 2nd team, Defense Agency for Technology and Quality) ;
  • Rho, Shin Baek (Daegu 2nd team, Defense Agency for Technology and Quality)
  • 정윤식 (국방기술품질원 대구2팀) ;
  • 노신백 (국방기술품질원 대구2팀)
  • Received : 2014.05.07
  • Accepted : 2014.12.01
  • Published : 2015.01.01

Abstract

In this paper, The ET-MBEF algorithm is presented for CCD imaging seeker. At the imaging seeker, target size information is important factor for accurate tracking. The MBEF algorithm was proposed to estimate target size at IIR seeker. However, the MBEF algorithm can't be applied at CCD imaginary target size estimation. In order to overcome the problem, we propose ET-MBEF algorithm which based on ET (Edge Template) and MBEF algorithm. The performance of proposed method is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target intercept performance.

Keywords

References

  1. L. Qi and Z. Shi, "A method for FLIR target tracking based on distance updating," 2008 Congress on Image and Signal Processing, May 2008.
  2. E. Trucco and A. Verri, Introductory Techniques for 3-D Computer Vision, Prentice Hall, 1998.
  3. Y. Jung, S. S. Lee, and S. B. Rho, "A study on the target tracking algorithm based on the target size estimation," Journal of Institute of Control, Robotics and Systems, vol. 20, no. 1, Jan. 2014.
  4. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Academic Press, New York, 1988.
  5. Y. Bar-Shalom and X. R. Li, Estimation and Tracking: Principles and Techniques and Software, Artech House, Inc, 1993.
  6. T. L. Song, D. G. Lee, and J. H. Ryu, "A probabilistic nearest neighbor filter algorithm for tracking in a clutter environment," Signal Processing, vol. 85, no. 10, Oct. 2005.
  7. T. L. Song and D. G. Lee, "A probabilistic nearest neighbor filter algorithm for m validated measurements," IEEE Trans. on Signal Processing, Jul. 2006.
  8. K. J. Rhee and T. L. Song, "A probabilistic strongest neighbor filter algorithm based on number of validated measurement," JSASS 16th International Sessions in the 40th Aircraft Symposium, Japan, Oct. 2002.
  9. T. L. Song, Y. T. Lim, and D. G. Lee, "A probabilistic strongest neighbor filter algorithm for m validated measurements," IEEE Trans on AES, vol. 48, no. 4, pp. 431-442, Apr. 2009.
  10. T. L. Song and D. S. Kim, "Highest probability data association for active sonar tracking," The 9th International Conference on Information Fusion, Jul. 2006.
  11. Y. S. Jung and T. L. Song, "A study of IIR target detection and tracking with feature based HPDA," The Korea Institute of Military Science and Technology (in Korean), vol. 11, no. 4, pp. 124-132, Jun. 2008.