Algorithm for estimating the energy distribution of radar signals scattering on acoustic disturbances created by UAVs - Kartashov, V.М.; Pososhenko, V.A.; Kolesnik, K.V.; Kolesnik, V.I.; Bobnev, R.I.; Kapusta, A.I. (Radiotekhnika, 2022)
The task of estimating the energy distribution over the observation interval of radar signals scattered on atmospheric inhomogeneities, arising as a result of UAV operation, is considered. The solution to this problem is necessary to improve detection algorithms, to classify the detected UAVs according to additional informational features, to improve the resolution when detecting several devices located at the same range during the group application of UAVs, to clarify the time parameters of the evolution of the movement of UAVs in time and space. A similar problem arises due to the need to process useful radar signals with a low signal-to-noise ratio in order to achieve the maximum possible range of reliable UAV detection. Because of this, it becomes impossible to estimate directly the energy of useful signals by the method of comparison with reference physical quantities due to a large measurement error. Therefore, an evaluation algorithm is proposed, based on the methods of the theory of ordinal statistics, which provide, instead of comparing numerical realizations with a certain standard, to form a variational series from them under the condition of a priori knowledge of the distribution function of these realizations. At the same time, the fact is used that for certain distributions of a random variable, among which there are normal and all limited ones, the variance of the estimate in the form of a mathematical expectation of certain ordinal statistics is significantly less than the variance of a direct measurement at a low signal-to-noise ratio. In order to save time and computing resources during real-time processing of received signals, it is proposed to use pre-calculated arrays of numerical values of mathematical expectation and dispersion of ordinal statistics for various parameters of the density distribution of a random variable.