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In this paper, a microstrip Wilkinson power divider (MWPD) based on particle swarm optimization (PSO) algorithm is designed, simulated, and fabricated using novel resonators. In addition, attenuators and open-ended stubs are incorporated to generate a broad cut-off band and reduce unwanted harmonics. The proposed power divider has a central frequency of 1 GHz. The performance of each used resonator is analyzed based on lumped-element circuit models.The L and C parameters of the equivalent circuit of the used resonators are predicted and optimized with the assistance of the PSO method. The subsequent phase was the fabrication of the proposed MWPD, after which its performance was evaluated in the light of the results obtained from the simulation. It was discovered that there was a high degree of concordance between the two. On the other hand, the fabricated circuit has several benefits, including a suitable S12 of − 3.15 dB, a high return loss of less than − 24 dB at the operating frequency, a compact size of 0.058 $${\varvec{\lambda}}_{{\varvec{g}}}$$ λ g × 0.064 $${\varvec{\lambda}}_{{\varvec{g}}}$$ λ g , and the ability to remove undesired harmonics. The results show a high level of suppression of the unwanted harmonics (up to the 16th harmonic) and a great responsiveness in the passband, while having very low ripple. As a result, the proposed circuit may be used in a wide variety of electronic devices, such as radar transmitter and receiver circuits, and many other high-frequency systems.
In this paper, a microstrip Wilkinson power divider (MWPD) based on particle swarm optimization (PSO) algorithm is designed, simulated, and fabricated using novel resonators. In addition, attenuators and open-ended stubs are incorporated to generate a broad cut-off band and reduce unwanted harmonics. The proposed power divider has a central frequency of 1 GHz. The performance of each used resonator is analyzed based on lumped-element circuit models.The L and C parameters of the equivalent circuit of the used resonators are predicted and optimized with the assistance of the PSO method. The subsequent phase was the fabrication of the proposed MWPD, after which its performance was evaluated in the light of the results obtained from the simulation. It was discovered that there was a high degree of concordance between the two. On the other hand, the fabricated circuit has several benefits, including a suitable S12 of − 3.15 dB, a high return loss of less than − 24 dB at the operating frequency, a compact size of 0.058 $${\varvec{\lambda}}_{{\varvec{g}}}$$ λ g × 0.064 $${\varvec{\lambda}}_{{\varvec{g}}}$$ λ g , and the ability to remove undesired harmonics. The results show a high level of suppression of the unwanted harmonics (up to the 16th harmonic) and a great responsiveness in the passband, while having very low ripple. As a result, the proposed circuit may be used in a wide variety of electronic devices, such as radar transmitter and receiver circuits, and many other high-frequency systems.
The phase diversity (PD) algorithm based on population optimization has been widely used in wavefront sensing due to advantages such as a simple optical path, no customized sensors, and low cost. However, this method requires a large amount of computation, and the optimization process is seriously disturbed by local extreme values, with the calculation time increasing with the size of the population. Therefore, it is unsuitable for scenarios with limited computing power and energy consumption, such as space optical systems. The field programmable gate array (FPGA) is a device widely used in the aerospace field with high flexibility, reconfigurability, high reliability, and low power consumption. Based on the characteristics of FPGA parallel computing, this paper analyzes and improves the phase diversity algorithm and the particle swarm optimization (PSO) used for its solution, making it suitable for a parallel algorithm architecture, and finally realizing FPGA board-level verification. The results show that this work can improve the computational speed and performance of the phase diversity algorithm based on population optimization.
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