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Performance Analysis of Monopulse System Based on Third-Order Taylor Expansion in Additive Noise

부가성 잡음이 존재하는 모노펄스 시스템 성능의 3차 테일러 전개 기반 해석적 분석

  • Ham, Hyeong-Woo (Department of Information and Communication Engineering, Sejong University) ;
  • Kim, Kun-Young (Department of Electrical Engineering, Sejong University) ;
  • Lee, Joon-Ho (Department of Information and Communication Engineering, Sejong University)
  • 함형우 (세종대학교 정보통신공학과) ;
  • 김건영 (세종대학교 전자정보통신공학과) ;
  • 이준호 (세종대학교 정보통신공학과)
  • Received : 2021.09.03
  • Accepted : 2021.12.20
  • Published : 2021.12.28

Abstract

In this paper, it is shown how the performance of the monopulse algorithm in the presence of an additive noise can be obtained analytically. In the previous study, analytic performance analysis based on the first-order Taylor series and the second-order Taylor series has been conducted. By adopting the third-order Taylor series, it is shown that the analytic performance based on the third-order Taylor series can be made closer to the performance of the original monopulse algorithm than the analytic performance based on the first-order Taylor series and the second-order Taylor series. The analytic MSE based on the third-order Taylor approximation reduces the analytic MSE error based on the second-order Taylor approximation by 89.5%. It also shows faster results in all cases than the Monte Carlo-based MSE. Through this study, it is possible to explicitly analyze the angle estimation ability of monopulse radar in an environment where noise jamming is applied.

본 논문은 가산성 잡음이 존재할 경우 모노펄스 알고리즘의 성능분석을 해석적으로 분석한 연구이다. 이전 연구에서는 1차 테일러 급수 전개와 2차 테일러 급수 전개를 통한 진폭비교 모노펄스 알고리즘의 해석적 성능 분석을 진행했다. 본 연구에는 3차 테일러 전개기반 해석적 분석법을 적용하여 1차 및 2차 테일러 근사기반의 해석적 분석보다 실제 모노펄스 알고리즘의 성능 분석 결과에 다가가는 것을 보인다. 성능분석은 평균제곱오차(Mean Squre Error)을 통해 분석되며 몬테카를로(Monte-Calro) 방법을 통한 시뮬레이션 MSE와 3차 테일러 근사기반 해석적 MSE를 서로 비교한다. 3차 테일러 근사기반 해석적 MSE를 적용하였을 경우, 이전 연구에서 제안된 2차 테일러 근사기반의 해석적 MSE의 오차를 89.5% 감소시킨다. 또한 몬테카를로 기반 MSE보다 모든 경우에서 빠른 결과를 보인다. 해당 연구를 통해 잡음 재밍이 적용된 환경에서 모노펄스 레이더의 추정 각도 능력을 명시적으로 분석이 가능하다.

Keywords

Acknowledgement

The authors gratefully acknowledge the support from Electronic Warfare Research Center at Gwangju Institute of Science and Technology (GIST), originally funded by Defense Acquisition Program Administration (DAPA) and Agency for Defense Development (ADD).

References

  1. S. M. Sherman & D. K. Barton. (1984). Monopulse principles and techniques, Artech House. Inc., Dedham, MA.
  2. A. I. Leonov & K. I. Fomichev. (1986). Monopulse radar. Foreign Technology Div Wright-Patterson Afb Oh.
  3. D. R. Rhodes. (1980). Introduction to monopulse. McGraw-Hill.
  4. B. R. Mahafza. (2013). Radar systems analysis and design using MATLAB. Chapman and Hall/CRC.
  5. M. A. Richards, J. A. Scheer, & W. A. Holm. (2008). Principles of modern radar basic principles. SciTech Publishing Inc, vol. 1, DOI : 10.1049/sbra021e
  6. R. C. Davis, L. E. Brennan & L. S. Reed, (1976). Angle estimation with adaptive arrays in external noise fields. IEEE Transactions on Aerospace and Electronic Systems, (2), 179-186. DOI : 10.1109/TAES.1976.308293
  7. D. J. An & J. H. Lee. (2020). Performance analysis of amplitude comparison monopulse direction-of-arrival estimation. Applied Sciences, 10(4), 1246. DOI : 10.3390/app10041246
  8. Y. J. Han, J. W. Kim, S. R. Park & S. U. Noh. (2017). An investigation into the monopulse radar using tx-rx simulator in electronic warfare settings. In Proceedings of the Symposium of the Korean Institute of communications and Information Sciences, Jeongseon, Korea (pp. 705-706). http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07125974
  9. Encyclopedia of Mathematics. (2013). Taylor Series(Online). https://encyclopediaofmath.org/wiki/Taylor_series
  10. Wikipedia. (2021) Normal distribution(Online). https://en.wikipedia.org/wiki/Normal_distribution