Direction-of-Arrival Estimation for a Random Sparse Linear Array Based on a Graph Neural Network.

This article proposes a direction-of-arrival (DOA) estimation algorithm for a random sparse linear array based on a novel graph neural network (GNN). Unlike convolutional layers and fully connected layers, which do not interact well with information between different antennas, the GNN model can adapt to the goniometry problem of non-uniform random sparse linear arrays without any prior information by applying neighbor nodes' aggregation and update operations. This helps the model in learning signal features under complex environmental conditions. We train the model in an end-to-end way to reduce the complexity of the network. Experiments are conducted on the uniform and sparse linear arrays for various signal-to-noise ratio (SNR) and numbers of snapshots for comparison. We prove that the GNN model has superior angle estimation performance on arrays with large sparsity that cannot be used by traditional algorithms and surpasses existing deep learning models based on convolutional or fully connected structures. The proposed algorithm shows excellent DOA estimation performance under the complex conditions of limited snapshots, low signal-to-noise ratio, and large array sparsity as well. In addition, the algorithm has a low time calculation cost and is suitable for scenarios that require low latency.

Optimization Based on the Surface Plasmon Optical Properties of Adjustable Metal Nano-Microcavity System for Biosensing.

This paper mainly studies the plasma optical properties of the silver nanorod and gold film system with gap structure. During the experiment, the finite element analysis method and COMSOL Multiphysics are used for modeling and simulation. The study changes the thickness of the PE spacer layer between the silver nanorod and the gold film, the conditions of the incident light and the surrounding environment medium. Due to the anisotropic characteristics of silver nanorod, the microcavity system is extremely sensitive to the changes of internal and external conditions, and the system exhibits strong performance along the long axis of the nanorod. By analyzing the extinction spectrum of the nanoparticle and the electric field section diagrams at resonance peak, it is found that the plasma optical properties of the system greatly depend on the gap distance, and the surrounding electric field of the silver nanorod is confined in the gap. Both ends of the nanorod and the gap are distributed with high concentrations of hot spots, which reflects the strong hybridization of multiple resonance modes. Under certain excitation conditions, the plasma hybridization behavior will produce a multi-pole mode, and the surface electric field distribution of the nanorod reflects the spatial directionality. In addition, the system is also highly sensitive to the environmental media, which will cause significant changes in its optical properties. The plasma microcavity system with silver nanorod and gold film studied in this paper can be used to develop high-sensitivity biosensors, which has great value in the field of biomedical detection.