Assessment of the reliability of statistical modeling of meteorological phenomenon parameters during digital field tests of radar systems


Аuthors

Bezuglov A. A.1*, Gavrilov K. Y.2**

1. PJSC UAC Sukhoi Design Bureau, 23A, Polikarpova str., Moscow, 125284, Russia
2. Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia

*e-mail: bezuglov_70@mail.ru
**e-mail: gvrk61@mail.ru

Abstract

The assessment of the main functional characteristics of meteorological radar systems (MRS) in the near-airfield zone is associated with the need to conduct numerous field tests under various operating conditions. Conducting field tests leads to long testing periods and significant financial costs. 
One of the most effective ways to reduce the testing time of radar systems is the digital-natural method of evaluating the characteristics of systems based on statistical modeling of input signals corresponding to various types of meteorological phenomena. This article describes the developed methodology for assessing the reliability of statistical modeling of meteorological phenomena parameters during digital-natural testing of radar systems. Since mathematical modeling can significantly reduce the testing time for MRS, the issue of the reliability of its results becomes very important.
It is assumed that the results of the measurements are such parameters of meteorological phenomena as radar reflectivity of meteorological objects, their radial velocity, the width of the Doppler spectrum of radial velocities, the specific rate of attenuation of turbulent energy, etc. Under the conditions of conducting experiments, in other words, the conditions of testing the MRS, the geographical location of the MRS, the season of the time of year of the test, etc.
The proposed method of assessing the reliability consists of two stages. In the first stage, the reliability of the experimental results is assessed separately for each combination of factors (conditions). The purpose of this stage is to discard outliers, or anomalous data, using the Thompson rule. In this process, unreliable experimental results are discarded and removed from further analysis. It is important to note that the reliability assessment of experimental results is performed for data obtained from both field tests and statistical modeling. In the first stage of data processing, it is assumed that the simulation results have a Gaussian distribution characterized by two parameters: the mean value and the variance, for which sample estimates are calculated. According to the Thompson rule, abnormal measurements are discarded by thresholding the normalized statistics.
At the second stage, the reliability of the results of statistical modeling of meteorological phenomena is estimated by testing the hypothesis of the identity of the probability distribution of two samples – a sample based on modeling and a sample based on field tests. The test of this hypothesis is performed based on the Kolmogorov-Smirnov test of goodness of fit, which compares the statistics in the form of the norm of the difference between two empirical distributions with a threshold selected based on a given significance level.
All numerical calculations were performed in the Matlab environment using standard functions for the Thompson and Kolmogorov-Smirnov criteria.
The paper provides an example of the analysis of digital-field tests corresponding to the results of statistical modeling and field experiments. The conditions for conducting field tests of the MRS, as well as the types and parameters of the meteorological phenomena studied, are described. The significance level values were set in the range of 0.01...0.1. It is shown which experimental results should be discarded and how valid the hypothesis of the identity of two samples is at the specified significance level. The obtained modeling results indicate the adequacy of the signal models to the real values. Thus, by statistical modeling of signals of various meteorological phenomena, it is possible to evaluate various tactical and technical characteristics of the MRS, such as the probabilities of detecting various meteorological phenomena and the accuracy of estimating their parameters. The degree of adequacy of the modeling results depends on the selected threshold values in the first stage of the reliability assessment and the significance level in the second stage of the reliability assessment.

Keywords:

meteorological radar complex, digital field experiment, meteorological phenomena, statistical modeling, criterion of agreement

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