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[Display omitted] • A high-gain circularly polarized magnetoelectric dipole antenna array for millimeter-wave is proposed. • An antenna array design method of trade-off between high gain and low profile is proposed in this paper. • The 4 × 4 antenna array achieves 20.4 dBic peak right-handed circularly polarized gain. A high-gain circularly polarized (CP) magnetoelectric (ME) dipole antenna with metallic radiating structure is presented. The proposed CP antenna element consists of two pairs of metallic posts with a supporting metallic plate, a metallic air-filled elliptical cavity, and a feeding slot on the bottom substrate integrated waveguide (SIW). The two pairs of modified rectangular metallic posts combined with the gaps between them act as radiating ME-dipoles which are surrounded by a metallic air-filled elliptical cavity. The above-mentioned radiating structures are fed by a modified cross-shaped coupling slot etched on the bottom feeding SIW to generate CP radiation, where loading the elliptical metallic cavity significantly improve the CP performance of the antenna element. Then, a 4 × 4 antenna array with full-corporate feeding network is designed, fabricated, and measured, which has an impedance bandwidth of 18.9 % from 37.4 to 45.2 GHz and a 3-dB axial ratio (AR) bandwidth of 14.2 % from 36 to 41.5 GHz. Thanks to the all-metal radiating structures, a maximum measured gain of 20.4 dBic has been achieved. The measured and simulated results are in good agreement. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel approach to address the challenge posed by large datasets in the context of antenna optimization through machine learning (ML). The approach involves a modified artificial neural network (ANN) technique. To tackle the issue of training with limited data, we introduce a method that leverages prior knowledge to create initial small datasets. Throughout the training process, these datasets are iteratively enhanced by incorporating new simulation data obtained from optimization results. In the applications presented here, ANN is used to establish a relationship model between antenna geometric variables and transmission coefficients (S 21). Subsequently, a genetic algorithm (GA) is used to optimize the decoupling of the antenna array. By implementing wideband and narrowband optimization of the S 21 between two antennas, the accuracy and efficiency of this method are verified. The initial design and optimized antennas were fabricated and measured. In summary, this proposed method not only can effectively mitigate the expenses associated with design but also generates antenna optimization solutions of high quality. [ABSTRACT FROM AUTHOR]

The measurement system of contact spherical actuator has the disadvantages of large friction resistance and poor rotor positioning accuracy. The structure or calculation of non-contact attitude measurement system is complicated. In order to solve the above problems, a multi-to-one wireless power transmission (WPT) spherical actuator attitude measurement method is proposed. The model of mutual inductance(MI) is built. This method effectively shortens the time of finite element analysis(FEA). Three motion states (spin, yaw and tilt) of actuator rotor are analyzed by using this measurement method. Compared with the micro electro mechanical system (MEMS) and fast complementary filter (FCF), the initial attitude error of this method is about 50% of that of the other two methods. Compared with MEMS method, the average angle error of WPT method is reduced by 35%. Experimental results show that this method has good real-time performance and repeatability. [ABSTRACT FROM AUTHOR]