An ultra-wideband (UWB) multiple-input, multiple-output (MIMO) antenna with a reasonably compact size of 30 × 18 × 1.6 mm³ is presented in this paper. The proposed antenna contains two radiating components, each of which is made up of three elliptically shaped patches situated 60 degrees apart, and resembles the shape of a flower. Moreover, the proposed antenna design incorporates a T-like ground branch that functions as a decoupling structure, and is composed of two modified inverted-L branches and an I-shaped stub, offering an isolation of more than 20 dB over the whole operation band (4.3–15.63 GHz). Furthermore, the proposed antenna system was fabricated and tested, and the envelope correlation coefficient (ECC), diversity gain (DG), and total active reflection coefficient (TARC), as well as the radiation characteristics and MIMO performance, were analyzed. The proposed UWB-MIMO antenna may be a suitable candidate for diverse UWB applications, based on the simulated and measured results of this study.

In this study, a novel characteristic mode basis function construction method is proposed to solve the problems of low efficiency and slow convergence of the iterative solution of the characteristic mode method. First, the characteristic modes (CMs) of each extended block are calculated separately by dividing objects, the CMs construction efficiency is improved for the decreased matrix dimensionality. Next, the effective CMs are selected as basis functions according to the modal significances. Finally, to improve the poor conditional number of the reduced matrix for the block extension, the singular value decomposition is used to enhance the orthogonality among these basis functions. Several numerical calculations show that the proposed method has significant efficiency and accuracy.

Establishing an effective evaluation model to analyze the actual environmental level of the multi-indicator systems is an urgent challenge. However, due to the complexity of the environmental system, the factors that determine the practical system are usually interrelated. To solve this problem, many methods have been proposed and verified. However, the disadvantage of unreasonable weight determination and only single-indicator assessment limits the practical application of these analysis methods. Here, we established an optimized entropy weight model and integrate it with the fuzzy comprehensive evaluation (FCE) method to quantify the complex environmental system. By introducing the linear programming method into the entropy weight solution, we can obtain high accuracy weight values and strong resistance to extreme data. Theoretical and simulation results demonstrate that our method can enhance the precision of weight calculation and evaluation results for multi-factor systems. Our work develops an effective method to quantify the complex environment system comprehensively and is significant to real applications of evaluation method.