Arrays of antenna elements orchestrated to act as a single antenna aperture offer a flexible platform for active electronic sensors and communication systems. Given the cost and complexity of these systems, there is a desire to increase the functionality of a single array to satisfy the needs of multiple functions including commu-nications, radar and electronic warfare (EW) functions. Today, while the RF front-ends are becomming simulta-neously integrated, reconfigurable, and capable of wide-band sampling, multifunction arrays are absorbing the concepts of dynamic spectrum access. The implementation of mechanisms in the domain of machine learning are more attractive now than ever. This case study addresses the need to articulate the trade-offs associated with a re-ward function encountered in reinforcement learning (RL) strategies applied to a multifunction phased array. The cri-teria considered include signal-to-interference plus noise, signal bandwidth, and electromagnetic compatibility. This study uses a multiobjective optimization genetic algorithm to estimate the Pareto frontier followed by multicriteria decision analysis to rank the solutions, specifically for the radar application.


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    Titel :

    Spectral Decision Support for Multifunction Phased Array Systems with Multiobjective Optimization


    Beteiligte:


    Erscheinungsdatum :

    15.07.2024


    Format / Umfang :

    960725 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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