DOI QR코드

DOI QR Code

Artillery Error Budget Method Using Optimization Algorithm

최적화 알고리즘을 활용한 곡사포의 사격 오차 예측 기법

  • Received : 2017.03.04
  • Accepted : 2017.08.30
  • Published : 2017.09.30

Abstract

In R&D of artillery system, error budget method is used to predict artillery firing error without field firing test. The error budget method for artillery has been consistently developed but apply for practical R&D of the weapon system has been avoided because of lacks of error budget source information. The error budget source is composed of every detailed error components which affect total distance and deflection error of artillery, and most of them are difficult to be calculated or measured. Also with the inaccuracy of source information, simulated error result dose not reflect real firing error. To resolve that problem, an optimization algorithm is adopted to figure out error budget sources from existing filed firing test. The method of finding input parameter estimation which is commonly used in aerodynamics was applied. As an optimization algorithm, CMA-ES is used and presented in the paper. The error budget sources which are figured out by the presented method can be applied to compute ROC of new weapon systems and may contribute to an improvement of accuracy in artillery.

곡사포의 사격오차는 탄착의 분산도와 탄착중심오차(MPI)를 포괄하는 용어로, 본 연구에서는 사격시험을 수행하지 않고 정량적 분석을 통해 사격오차를 예측하는 기법에 대해 논하고자 한다. 기존에도 곡사포의 사격오차를 예측하기 위한 분석기법은 있었지만, 오차에 관여하는 영향요소들에 대한 정보가 부족하여 활용이 제한되었다. 본 연구에서는 이런 문제를 해결하기 위해 누적된 시험이 수행된 기존 무기체계 시험결과를 활용하여, 오차의 원인이 되는 각 요소 값들을 역으로 산출하는 방식을 제안한다. 이 과정에서 항공공학 분야에서 흔히 사용되는 최적화 알고리즘을 이용한 입력계수 추출 방식을 도입하였다. 최적화 알고리즘으로는 CMA-ES라는 진화적 기법을 소개하며, 적용 결과에 대하여 해설하였다. 이런 과정을 통해 얻은 사격오차요인 값은 향후 신규 무기체계 개발에 있어 성능요구사항 산출에 사용될 수 있으며, 야전에서의 곡사포 정확도 향상에도 기여할 것으로 보인다.

Keywords

References

  1. Driels, Morris R. "Weaponeering: Conventional Weapon System Effectiveness, Reston, VA: American Institute of Aeronautics and Astronautics." (2004).
  2. Fann, Chee M. Development of an artillery accuracy model. NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF MECHANICAL AND ASTRONAUTICAL ENGINEERING, 2006.
  3. Wessam, M. E., and Z. H. Chen. "Firing Precision Evaluation For Unguided Artillery Projectile." Proc. of International Conference on Artificial Intelligence and Industrial Engineering. 2015.
  4. Lim, Wee Yeow. Predicting the accuracy of unguided artillery projectiles. Diss. Monterey, California: Naval Postgraduate School, 2016.
  5. Gross, Matthew, and Mark Costello. "Projectile Parameter Estimation Using Meta-Optimization." AIAA Atmospheric Flight Mechanics Conference. 2016
  6. Singh, Sanjay, and A. K. Ghosh. "Parameter estimation from flight data of a missile using maximum likelihood and neural network method." Proceedings of AIAA Flight Mechanics Conference and Exhibit, Colorado, USA: AIAA Press. 2006.
  7. Guan, Jun, et al. "Aerodynamic Parameter Estimation of a Symmetric Projectile Using Adaptive Chaotic Mutation Particle Swarm Optimization." Mathematical Problems in Engineering 2016 (2016).
  8. Iliff, Kenneth W. "Parameter estimation for flight vehicles." Journal of Guidance, Control, and Dynamics 12.5 (1989): 609-622. https://doi.org/10.2514/3.20454
  9. Eung Tai Kim, Kie-Jeong Seong, Yeong-Cheol Kim. "A Study on Parameter Estimation for General Aviation Canard Aircraft." International Journal of Aeronautical and Space Sciences, 16.3 (2015.9): 425-436. Print. https://doi.org/10.5139/IJASS.2015.16.3.425
  10. Hansen, Nikolaus, and Stefan Kern. "Evaluating the CMA evolution strategy on multimodal test functions." International Conference on Parallel Problem Solving from Nature. Springer Berlin Heidelberg, 2004.