This paper presents an approach for identifying the optimal configuration of avionic systems of the unmanned aerial vehicle (UAV) based on an additive multi-attribute utility function. The function arguments are technical and economic indicators of avionics design quality that are specified in accordance with the UAV requirements. The method is developed on an improved decision model that has a high degree of adequacy primarily by the increasing number of the utility attributes and using advanced reliability models of avionic systems. These reliability models consider in addition to the reliability parameters of main and standby elements of fault-tolerant units the effectiveness of non-perfect detection and switching devices. The proposed method enables the increasing certainty of design analysis results. It allows determining the optimal configurations of the avionic systems and rational maintenance regime ensuring needed effectiveness and reliability, minimizing the expenditure of resources.

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Signal-code constructions with modulating binary sequences are widely used in multichannel radiocommunication systems, radar, and other information systems. Among these sequences, there are those that provide the minimum levels of side lobes of the aperiodic autocorrelation function and, accordingly, the required secrecy, noise immunity, resolution, and other important characteristics and parameters. The paper describes an alternative approach for solving optimization task that involves a complete full search for the optimal binary skew-symmetric sequences with odd dimension l using a criterion of minimum side lobes of the aperiodic autocorrelation function. The proposed method based on performing two consecutive steps: optimizing in the space of dimension L < 0.5(l − 5) of the objective functions with respect to the levels of side lobes of the aperiodic autocorrelation function and solving of an equation system which specifies the aperiodic autocorrelation function. The right sides of the equation system present the levels of the side lobes that are obtained as the result of completing the first operation. The developed methodology includes an analysis of the structure of sets of binary sequences; finding correlations between the structural components using the methods of group theory; establishing analytical forms that define the functional relationships between the levels of side lobes of the aperiodic autocorrelation function. The article presents an example of application and results of modeling of the offered algorithm to identify optimal binary sequences.