Methodology of statistical synthesis and analysis methods for stochastic signal processing in multi-antenna radio direction finders

The subject of this study is the development of a statistical synthesis methodology and analysis methods for processing stochastic signals in multi-antenna radio direction finders. The aim of this study is to improve the accuracy, stability, and adaptability of these systems under changing operating conditions, especially for applications involving unmanned aerial vehicles. The objectives of the study are: 1) formulation of analytical models of signals and noise with specified statistical characteristics; 2) determination of the criteria for the maximum likelihood function for solving optimisation problems; 3) creation of a basis for estimating marginal errors of measuring the angular positions of radio sources emitting stochastic signals; 4) development of a structural diagram of a radio direction finding system based on the obtained algorithm; 5) simulation modelling of the direction finder. The methods for solving the tasks are statistical theories of radio engineering systems, simulation modelling and optimisation in the spectral domain to solve the problems of designing radio direction finders capable of processing stochastic signals. This approach allows for the integration of amplitude and phase measurements for multiple antennas, ensuring compatibility with UAV-specific constraints, such as size, weight, and aerodynamic characteristics. The following results were obtained: 1) theoretical foundations for optimising radio direction finders for stochastic signals, validated by simulation and analytical modelling; 2) algorithms and block diagrams for a prototype single-antenna non-scanning radio direction finder, demonstrating the proposed methodology; 3) experimental verification confirming the feasibility of the proposed methods. This work provides a way for further development of multi-antenna direction-finding technologies, offering scalable solutions for use in UAVs and allowing accurate estimation of signal parameters under conditions of uncertainty. Future directions include the extension of the methodology to dual-antenna systems, hybrid configurations, and spatially distributed multi-antenna systems.