Joint Optimization of Sum and Difference Patterns with a Common Weight Vector Using the Genetic Algorithm

• Autorzy: Mohammed Jafar Ramadhan , Aljaf Duaa Alyas

Identyfikatory

DOI

10.26636/jtit.2022.160722

• Języki publikacji: EN

Abstrakty

EN

A monopulse searching and tracking radar antenna array with a large number of radiating elements requires a simple and efficient design of the feeding network. In this paper, an effective and versatile method for jointly optimizing the sum and difference patterns using the genetic algorithm is proposed. Moreover, the array feeding network is simplified by attaching a single common weight to each of its elements. The optimal sum pattern with the desired constraints is first generated by independently optimizing amplitude weights of the array elements. The suboptimal difference pattern is then obtained by introducing a phase displacement π to half of the array elements under the condition of sharing some sided elements weights of the sum mode. The sharing percentage is controlled by the designer, such that the best performance can be met. The remaining uncommon weights of the difference mode represent the number of degrees of freedom which create a compromise difference pattern. Simulation results demonstrate the effectiveness of the proposed method in generating the optimal sum and suboptimal difference patterns characterized by independently, partially, and even fully common weight vectors.

Słowa kluczowe

EN

common weight vector; difference pattern; genetic algorithm; monopulse radar antenna; sum pattern

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2022
• Tom: nr 3
• Strony: 67--73
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Mohammed Jafar Ramadhan

• Ninevah University, Mosul, Iraq

autor

Aljaf Duaa Alyas

• Mosul University, Mosul, Iraq

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).