Integrated frequency-based method for flight planning of stratospheric gliders with anomaly filtering
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Abstract
This paper presents, for the first time, an integrated method for flight planning of stratospheric gliders operating within swarm-based multilevel systems, which combines frequency analysis of time series of key flight performance indicators with an adapted Irwin criterion for filtering anomalous parameter deviations. The proposed approach enables the detection of long-period oscillations caused by stratospheric atmospheric processes and collective swarm dynamics, and allows for the timely identification of critical deviations that may disrupt swarm coordination, lead to additional energy losses, or cause degradation of the multilevel control system. The developed method is aimed at ensuring stability, adaptability, and energy efficiency of long-duration stratospheric soaring and can be applied to improve the effectiveness of flight planning for stratospheric gliders in multilevel autonomous systems. Existing approaches to flight planning for stratospheric vehicles are generally focused on local optimization of energy consumption or kinematic parameters and are based on the assumption of process stationarity. At the same time, most studies leave unresolved the issues of comprehensive analysis of the spectral structure of flight parameters, integration of frequency-domain methods into route evaluation procedures, and formalized detection of anomalies that may impair swarm coordination, accumulate energy losses, and degrade multilevel control systems. The objective of this study is to develop and substantiate an integrated algorithm for frequency analysis of flight planning indicators of stratospheric gliders in swarm-based multilevel systems using an adapted Irwin criterion for anomaly filtering. The proposed algorithm is intended to improve the accuracy of assessing long-period oscillations of flight parameters, enhance swarm interaction stability and energy efficiency of prolonged stratospheric soaring, and increase the reliability of multilevel autonomous control systems. The obtained results provide a scientific basis for the further development of adaptive control algorithms for swarm stratospheric gliders and may be used to improve the performance of autonomous multilevel systems in monitoring, communication, and surveillance applications.
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