Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Numerical Integration-based Performance Analysis of Amplitude-Comparison Monopulse System

진폭비교 모노펄스시스템의 수치적분 기반 성능분석

  • Ham, Hyeong-Woo (Department of Information and Communication Engineering, Sejong University) ;
  • Lim, Hee-Yun (Electrical Engineering, Sejong University) ;
  • Lee, Joon-Ho (Department of Information and Communication Engineering, Sejong University)
  • 함형우 (세종대학교 정보통신학과) ;
  • 임희윤 (세종대학교 전자정보통신공학과) ;
  • 이준호 (세종대학교 정보통신학과)
  • Received : 2021.10.13
  • Accepted : 2021.12.20
  • Published : 2021.12.28
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Abstract

In this paper, estimation angle performance analysis of amplitude-comparison monopulse radar under additive noise effect is dealt with. When uncorrelated white noises are added to the squinted beams, the angle estimation performance is analyzed through the mean square error(MSE). The numerical integration-based mean square error result completely overlaps the Monte Carlo-based mean square error result, which corresponds to 99.8% of the Monte Carlo-based mean square error result. In addition, the mean square error analysis method based on numerical integration has a much faster operation time than the mean square error method based on Monte Carlo. the angle estimation performance of the amplitude comparison monopulse radar can be efficiently analyzed in various noise environments through the proposed numerical integration-based mean square error method.

본 논문에서는 부가성 잡음이 존재하는 환경에서 진폭비교 모노펄스 레이더의 각도 추정 성능을 수치해석 기반으로 접근하여 분석한다. 편향 빔에 서로 상관이 없는 백색잡음이 추가되었을 때, 모노펄스 레이더의 각도 추정 성능을 평균제곱오차(MSE)를 통해 분석한다. 수치적분 기반의 평균제곱오차 결과는 몬테카를로 기반의 평균제곱오차 결과와 완벽히 겹치는 결과를 보이며 이는 몬테카를로 기반 평균제곱오차 결과에 99.8%에 해당한다. 또한 연산시간 측면에서 수치적분 기반의 평균제곱오차 분석법은 몬테카를로 기반의 평균제곱오차보다 매우 빠른 결과를 보인다. 따라서 제안된 수치적분 기반 평균제곱오차 방법을 통해 다양한 잡음환경에서 진폭비교 모노펄스레이더의 각도 추정 성능을 효율적으로 분석할 수 있다.

Keywords

Acknowledgement

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

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