이상전파 측정 데이터의 통계적 모델링 및 해석 알고리즘

Abstract

In this thesis, we consider new simulator for analyzing anomalous propagation using parabolic equation (PE) model. Existing algorithms using PE model can not assume mixed terrain, which consists of sea and land. In addition, they cannot reflect the fact that the height of terrains influences atmospheric refractive index. An improved PE simulator is proposed with real environment that includes various surface parameter at each split region. In addition, the atmospheric refractive indices are compensated according to terrain information from Jeju to Jindo, the simulated region in this thesis. Atmospheric refractive index profile is obtained by weather information in the Korea Meteorological Administration (KMA), and we use interpolation to construct full profile. We obtain path-loss data from the improved PE algorithm and compare them to the measured data. We compare the improved and existing simulator. Results show that there are no difference on performance between two simulators. In the next thesis, methods of statistically modeling path-loss of anomalous propagation are introduced. Existing methods are using path loss data from simuation. We used measured data instead of simulated data, and classified these data using the atmospheric refractive index profile. The method by using vertical gradient of refractivity is also introduced. Then, we evaluated these models by predicting path loss in some periods. Results show that predicted and measured path loss are not matching each other.