Identification of maneuvering objects during structural and system control of airspace

Работа посвящена построению процедуры идентификации маневрирующих объектов с использованием критерия идеального наблюдателя и фильтрации параметров трасс при сопровождении средствами мониторинга в интересах структурносистемного контроля воздушного пространства. Для минимизации среднеквадратических ошибок оценок координат и скоростей движения объектов разработаны алгоритмы экстраполяции параметров траекторий путем задания корректирующего шумового ускорения и замены результатов фильтрации оценок координат на измеренные значения при распознавании маневра. Обоснованы параметры фильтрации с шумовым ускорением в зависимости от точности измерений пространственных характеристик и идентификации при группировании однотипных признаков с наибольшими значениями условных вероятностей ситуаций отождествления объектов Purpose. This work addresses construction of the procedure for identifying maneuvering air objects in the process of tracking their routes. Monitoring tools during structural and system air space control are employed. The study is aimed to establish the abilities of correct identification of objects and false alarm at various standard errors of measurements of angular coordinates and to determine ways to increase efficiency of identifications performed due to selection of filtering options during trace tracking. Methodology. Identification of objects was performed according to the ideal observer criterion by comparing estimates of angular coordinates of objects subjected to linear filtering with corrective noise acceleration. In order to minimize root-mean-square errors of coordinates and motion velocity estimates of objects, route parameter extrapolation algorithms are obtained by setting correcting noise acceleration and replacing the results of filtering coordinate estimates with measured values during manoeuvre recognition. Due to a priori uncertainty of route parameters, target tracking was initially performed using recurring linear filtering while maintaining the priority of straight uniform movement. The recognition of the maneuver was carried out as a result of exceeding the difference between the measured and filtered values of the target coordinates of the threshold value. Findings. Filtering parameters with noise acceleration are justified depending on the accuracy of measurements of spatial characteristics and identification when grouping identification features with the highest values of conditional probabilities of situations for the objects under identification. As a result of replacing filtered parameters of alignments containing areas with rotations of 10 and 20, measured values for standard bearing errors (1 ... 2), the maximum error in determining directions for objects reaches 0.8 and 0.9, respectively. When replacing the estimates of the parameters of the alignments obtained using a recurring linear filter without taking into account noise acceleration, the coordinate values measured at the bearing error (0 . 5 ... 2), the errors of the filtered bearing of the targets at the angles of rotation of 10are (0 . 2 ... 1). When maneuvering objects with turns by 20, the largest value of the standard bearing error increases to 1.2. By increasing the accuracy of the diaper from 2 to 0.5, the probability of correct identification of objects in monitoring tools performing noise correction acceleration filtering increases by about 3 times and reaches a value of 0.9. As a result of replacing the estimates of the parameters of the alignments filtered taking into account the corrective noise acceleration with the results of measurements, the probability of correct identification of objects with standard bearing errors of not more than 0.5decreases from 0.9 to 0.85. Originality/value. The identification of maneuvering air objects is performed using filtering of route parameters calculated with the help of the ideal observer criterion. For the most efficient identification, the identification features belonging to the same object must be established according to the highest conditional probability of the identification situation. To minimize errors in estimation of the angular coordinates of objects, a procedure for filtering motion parameters with corrective noise acceleration is implemented