The performance of petal antennas is often hampered by deployment errors, a prominent form of error that has significant implications on radiation performance, and surface errors. Traditional calculation methods often overlook the relationship between errors on individual petals, thus leading to an overestimation of the interval calculation. This study presents a novel interval analysis method based on an ad hoc auxiliary formulation to effectively manage the influence of deployment angle error. The proposed methodology addresses the overestimation issue inherent in the interval estimation, offers a more straightforward computation process, and presents potential synergy with antenna shaping techniques to enhance antenna design. The validity and efficiency of this method are corroborated through several representative numerical examples.

In this communication, a new Taylor expansion-based interval pattern analysis method is developed to predict the impact of the small excitation amplitude uncertainty on the radiated array pattern. The dependence problem of the classical interval arithmetic, which may lead to overestimation of performance intervals, is addressed in this communication. The proposed method approximates by approximating the antenna power values to the first order with respect to the uncertain amplitude. The new method is simpler and can produce more accurate bounds of the antenna pattern and the pattern features than the existing techniques. Several representative numerical examples are investigated to demonstrate the validity and efficiency of the proposed method.

The inverse finite element method (iFEM) is one of the most effective deformation reconstruction techniques for shape sensing, which is widely applied in structural health monitoring. The distribution of strain sensors affects the reconstruction accuracy of the structure in iFEM. This paper proposes a method to optimize the layout of sensors rationally. Firstly, this paper constructs a dual-objective model based on the accuracy and robustness indexes. Then, an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm is developed for this model, which introduces initialization strategy, the adaptive inertia weight strategy, the guided particle selection strategy and the external candidate solution (ECS) set maintenance strategy to multi-objective particle swarm optimization (MOPSO). Afterwards, the performance of IAMOPSO is verified by comparing with MOPSO applied on the existing inverse beam model. Finally, the IAMOPSO is employed to the deformation reconstruction of complex plate-beam model. The numerical and experimental results demonstrate that the IAMOPSO is an excellent tool for sensor layout in iFEM.

The structural deformation of an array antenna could lead to degradation of its radiation performance, thus not meeting the engineering design requirements. There are many methods to compensate for the radiation pattern of deformed array antennas, but seldom do they take the mutual coupling (MC) effect into account. However, the MC effect is one of the important factors that cannot be neglected in practical application. In this letter, the MC effect of an array antenna is analyzed by network theory. In addition, a compensation method is proposed for deformed array antennas based on the electromechanical coupling analysis method and the least squares error approach. This method could be applied for the arrays with single-mode radiating elements. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.