2023/3

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    A Modified Vector Fitting Technique to Extract Coupling Matrix from S-parameters
    (Společnost pro radioelektronické inženýrství, 2023-09) Ng, C. L.; Soeung, S.; Cheab, S.; Leong, K. Y.
    In this paper, a modified vector fitting technique to extract coupling matrix from S-parameters is introduced. This work allows designers to extract the coupling matrix of different or any pre-defined topologies from the simulated or measured S-parameter data. A study on vector fitting (VF) equations that can extract the rational polynomial of bandpass filter responses is carried out. The rational polynomials are formed by applying the VF process to S-parameter responses without having to remove the phase offset and de-embedding the transmission lines. The desired coupling matrix configuration is generated directly from the extracted polynomials using unconstrained and finitely bounded non-linear polynomials (NLP) optimization. Without the need for matrix transformation, the matrix elements are still able to show a one-to-one relationship in coupling values of resonators. Two bandpass filters are shown as examples to illustrate the performance of the new variation of VF.
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    Study on the Generation of Vortex Waves Based on Coding Metasurfaces and Genetic Algorithms
    (Společnost pro radioelektronické inženýrství, 2023-09) Lv, S. Q.; Cao, X. Y.; Gao, J.; Xue, R. Z.
    In this paper, the mechanism of vortex electromagnetic wave generated by coding metasurface is studied, and the shortcomings of this method are found through the research, what is more, the reasons for its production are analyzed and summarized. The genetic algorithm is proposed to optimize the arrangement of the encoded metasurface, to improve the angle convergence between the main lobes of the vortex electromagnetic wave, which is conducive to the next transmission detection work. In order to verify this method, two units with phase difference of 180° are designed, and the vortex electromagnetic wave with orbital angular momentum of 1 is produced. Finally, the fabricated sample is measured, and the results are in good agreement with the simulation results.
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    Extended Target Fast Labeled Multi-Bernoulli Filter
    (Společnost pro radioelektronické inženýrství, 2023-09) Cheng, X.; Ji, H.; Zhang, Y.
    Focusing on the real-time tracking of the extended target labeled multi-Bernoulli (ET-LMB) filter, this paper proposes an extended target fast labeled multi-Bernoulli (ET-FLMB) filter based on beta gamma box particle (BGBP) and Gaussian process (GP), called ET-BGBP-GP-FLMB filter. First, a new ET-FLMB filter is derived to reduce the computational complexity of the ET-LMB filter. Then, by modeling the target state as an augmented state including detection probability, measurement rate, kinematic state and extension state, the BGBP-GP implementation of the ET-FLMB filter is presented. Compared with the traditional sequential Monte Carlo (SMC) implementation, the proposed implementation can not only greatly reduce the number of particles and the amount of computation, but also estimate the detection probabilities, measurement rates and extension states while estimating the number and kinematic states of extended targets. Finally, the simulation results show that the proposed filter can significantly reduce the computational burden and improve the real-time performance.
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    A Hybrid Adaptive Beamforming Algorithm for SINR Enhancement in Massive MIMO Systems
    (Společnost pro radioelektronické inženýrství, 2023-09) Manai, H.; Ben Hadj Slama, L.; Bouallegue, R.
    With the extreme density of devices and fast change of their directions in massive MIMO networks, a fast adaptive beamforming algorithm is required to provide high directivity and an enhanced signal-to-interference and noise ratio (SINR). Blind adaptive beamforming is suitable but less efficient, while non-blind adaptive beamforming is more efficient but requires significant training time. This study proposes a hybrid adaptive beamforming algorithm that addresses these issues. The algorithm integrates an improved direction-finding method to estimate the directions of arrival (DoAs) of incident signals at the antenna array, even in coherent signals cases, and a cascading combination of a blind and non-blind algorithms. The proposed algorithm generates an accurate main beam toward the desired direction and deep nulls in the direction of interfering signals, resulting in enhanced SINR. Compared to other algorithms, our approach achieves better performance without requiring additional antenna elements.
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    Spatial Localization of Electromagnetic Radiation Sources by Cascade Neural Network Model with Noise Reduction
    (Společnost pro radioelektronické inženýrství, 2023-09) Ilic, M.; Stankovic, Z.; Males-Ilic, N.
    In this paper, the Direction of Arrival - DoA estimation for two mobile sources was performed by using the Single Multilayer Perceptron (MLP) neural network model (SMLP-DoA) and the Cascade MLP model(CMLP). The latter model consists of two neural networks connected in a cascade where the outputs of the first MLP that rejects noise represent the inputs to the second network in a cascade. The outputs of the neural network models determine the direction of arrival of the incoming signals. Two cases were considered, in the first case the neural networks were trained on the samples that were without noise, and in the second with samples containing noise. Both considered neural network models were tested with noisy samples. The results of these two neural models are compared to the results achieved by the RootMUSIC algorithm. The presented results show that the proposed CMLP model has a higher accuracy in determining the angular positions of sources compared to the classical SMLP-DoA model and the RootMUSIC algorithm. Moreover, the CMLP model executes significantly faster compared to the model based on the RootMUSIC algorithm.