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Analyzing the Impact of Observation Errors in Counter-Battery Radar and Errors of Artillery on Firing Effectiveness

대포병탐지레이더의 관측오차와 화포 오차에 따른 사격효과도 분석

  • Received : 2023.05.17
  • Accepted : 2023.06.06
  • Published : 2023.06.30

Abstract

Unlike conventional radar, Counter-Battery radar encounters observation errors when estimating the target's location. These observation errors are among the main factors that decrease the effectiveness of hitting the enemy with artillery. The objective of this study is to analyze the impact of observation errors from Counter-Battery radar on firing effectiveness. Scenarios were assumed with enemy and friendly artillery ratios of 1:1, 1:6, and 6:6. The observation errors of Counter-Battery radar and artillery accuracy were each adjusted in increments of 1m within a range of 0-300m, and a Monte Carlo method was employed to conduct a simulation analysis on the firing effectiveness. Simulation analysis results confirmed that the observation errors of Counter-Battery radar impact the firing effectiveness as much as the errors in artillery. It was also found that the firing effectiveness can be improved depending on the way the artillery is operated. The findings of this research provide a quantitative analysis method for the military when determining the required performance in relation to observation errors of Counter-Battery radar. It is expected to contribute to enhancing the effectiveness of the current system operation, producing more realistic results in battlefield simulation analysis, among other benefits.

대포병탐지레이더는 일반적인 레이더와 달리 표적의 위치를 추정하는 데 관측오차가 발생한다. 관측오차는 화포로 적을 타격 시 효과도를 감소하는 주요 원인 중 하나이다. 본 연구의 목적은 대포병탐지레이더의 관측오차가 사격효과도에 미치는 영향을 분석하는 데 있다. 적군과 아군의 포병 비율을 1:1, 1:6, 6:6인 시나리오를 가정하였으며, 대포병탐지레이더의 관측오차와 화포의 오차를 각각 0~300m 범위에서 1m씩 조정하며 몬테카를로 방법을 활용하여 사격효과도 모의 분석을 수행하였다. 모의 분석 결과 대포병탐지레이더의 관측오차가 화포의 오차만큼 사격효과도에 영향을 미치는 것을 확인하였다. 그리고 화포를 운영하는 방법에 따라 사격효과도 또한 개선될 수 있는 것을 확인할 수 있었다. 연구의 결과는 대포병탐지레이더 관측오차에 대한 군의 요구성능 결정 시 정량적인 분석 방법을 제공하며, 현재 보유하고 있는 체계 운용 효과도 제고, 전장 모의 분석 수행 시 좀 더 실제와 가까운 분석 결과 도출 등에 기여할 것으로 기대한다.

Keywords

References

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