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Development of Simulation Method of Doppler Power Spectrum and Raw Time Series Signal Using Average Moments of Radar Wind Profiler

윈드프로파일러의 평균모멘트 값을 이용한 도플러 파워 스펙트럼 및 시계열 원시신호 시뮬레이션기법 개발

  • Received : 2020.10.25
  • Accepted : 2020.12.15
  • Published : 2020.12.31

Abstract

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

윈드프로파일러(RWP, radar wind profiler)는 기상 상태와 관계없이 시공간 분해능이 높은 바람장 자료를 제공하며 생산된 바람의 정확도나 품질에 대한 검증이 필수적이다. 기존 정확도 검증 방식은 레윈존데와의 동시 관측을 통해 윈드프로파일러에서 생성된 바람 벡터를 기준 자료로 활용하는 것이다. 본 연구에서는 평균 모멘트 자료로부터 스펙트럼과 원시 시계열 자료를 시뮬레이션하는 알고리즘을 통해 윈드프로파일러의 신호처리 알고리즘을 단계별로 검증하는 방안을 제시하고, LAP-3000의 원시 자료와의 비교를 통해 해당 알고리즘의 가능성을 확인하였다. 기상 신호의 밀도 함수를 모멘트값을 인자로 하는 왜곡된 정규 분포의 밀도 함수로 가정하여 생성하였고, 난수를 통해 시뮬레이션 스펙트럼을 생성하였다. 또한, 난수 위상과 역 이산푸리에 변환으로 간섭 평균된 시뮬레이션 원시 시계열 자료를 생성하고 최종적으로 디리클레 분포(Dirichlet distribution)를 통해 간섭 평균 전 단계의 원시 시계열 자료를 생성하였다.

Keywords

References

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