A new noniterative method for pattern synthesis of unequally spaced linear arrays

In this article, a new noniterative beam shaping method is introduced to synthesise array factor (AF) of an unequally spaced linear array (UESLA). The proposed method is based on eigenvector decomposition of sampled data matrix of a given pattern. Using matrix analysis, the eigenvalues and their corresponding eigenvectors of the sampled matrix are determined. It is shown that the eigenvalues and eigenvectors of the sampled matrix are related to the locations and complex excitation coefficients of the array elements. According to the concept of generalized eigenvalue concept, the solution of locations and excitation coefficients is derived using least square method. In order to reduce the number of array elements, singular value decomposition is applied to obtain a low ranked matrix using rejection of nonzero eigenvalues. Using the approximated sampled matrix, the excitation and locations of the optimized array elements are calculated. A few comprehensive examples are investigated to verify the accuracy of the proposed method and the obtained results are compared with those of an equally spaced linear array (ESLA). It is shown that the total number of array elements in an UESLA is less than that of ESLA, which is the most advantage of the introduced method in AF synthesis.     

Optimized element positions for prescribed radar cross section pattern of linear dipole arrays

Approximate closed‐form expression is derived for the scattering from dipole arrays based on the equivalent circuit theory. Then, a method is proposed for synthesis of dipole arrays to produce desired scattering pattern using genetic algorithm (GA). In the synthesis method, the element positions in an array are considered as the optimization parameter and the derived expression is used to evaluate the fitness function of GA. To assess the validity and efficiency of the proposed method, several linear dipole arrays are designed to obtain scattering pattern with low sidelobe level (SLL). A good agreement between the patterns calculated using the expression and simulated by FEKO validates the accuracy of the presented expression. In addition, the numerical results show that the maximum SLL of the scattering pattern is considerably reduced by optimization. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2011.     

共形球面阵建模及其旁瓣控制的研究

运用球面几何知识,根据孔径及最小阵元间距约束,提出了一种基于正二十面体球面三角剖分法的球面阵建模方法。应用遗传算法,针对新模型相对主瓣较高的旁瓣电平问题,以阵元位置标识向量为个体元素,进行孔径、阵元个数、最小间隔一定的稀疏优化处理。仿真结果表明,新模型在结构上实现了阵元的近似球面对称分布,运用遗传算法有效地优化了共形球面阵的旁瓣性能。     

A new hybridized backtracking search optimization algorithm with differential evolution for sidelobe suppression of uniformly excited concentric circular antenna arrays

In this work, a hybridized combination of backtracking search algorithm (BSA) with differential evolution (DE) is proposed and applied on sidelobe suppression problem of uniformly excited concentric circular antenna arrays (CCAA). Each array is assumed to have isotropic elements and be placed on x‐y plane and has one center element. A search for optimal setting of ring radius and number of elements in each ring is carried out so as to achieve low sidelobe performance on overall azimuth plane. Care has been taken so that directivity does not get degraded as far as possible. Before applying this algorithm to CCAA design problem, BSA and the hybridized algorithm BSA‐DE are tested on five complex benchmark functions. Based on 30‐independent runs for each benchmark function, Wilcoxon's pairwise signed ranks test is utilized to judge the relative search performance of these two algorithms. The hybridized algorithm proves its superiority on almost all the considered benchmark functions. For the CCAA design problem dealt with in this work, BSA‐DE shows its superiority on one or both pattern parameters as well as structural parameters. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:262–268, 2015.     

基于GA的仪表新产品功能结构方案推理机模型关键技术研究

虚拟原型逼真设计是近几年发展起来的新技术,主要研究虚拟环境下的产品建模问题以及基于仿真的集成产品和过程设计问题．产品功能结构方案推理机模型是虚拟原型逼真设计实现的关键技术之一．针对功能模块组合方案优化问题的复杂性,研究了基于遗传算法（GA）的功能结构方案推理机模型的实现技术,提出了双链异或杂交算子和自适应调节杂交概率和突变算子选择等算法,结合仪表产品设计应用实例,验证了模型的优越性,并将其应用于仪表新产品开发决策支持系统——仪表LC—QDPDS软件系统中．     

Soft Computing Based Pattern Classifiers for the Obstacle Avoidance Behavior of Intelligent Autonomous Vehicles (IAV)

To ensure more autonomy and intelligence with real-time processing capabilities for the obstacle avoidance behavior of Intelligent Autonomous Vehicles (IAV), the use of soft computing is necessary to bring this behavior near to that of humans in the recognition, learning, adaptation, generalization, reasoning and decision-making, and action. In this paper, pattern classifiers of spatial obstacle avoidance situations using Neural Networks (NN), Fuzzy Logic (FL), Genetic Algorithms (GA) and Adaptive Resonance Theory (ART) individually or in combination are suggested. These classifiers are based on supervised learning and adaptation paradigms as Gradient Back-Propagation (GBP), FL, GA and Simplified Fuzzy ArtMap (SFAM) resulting in NN/GBP and FL as Intelligent Systems (IS) and in NN/GA, NN/GA-GBP, NN-FL/GBP and NN-FL-ART/SFAM as Hybrid Intelligent Systems (HIS). Afterwards, a synthesis of the suggested pattern classifiers is presented where their results and performances are discussed as well as the Field Programmable Gate Array (FPGA) architectures, characterized by their high flexibility and compactness, for their implementation.     

A novel approach to hedge and compensate the critical dimension variation of the developed-and-etched circuit patterns for yield enhancement in semiconductor manufacturing

Linewidth control is critical for yield enhancement in semiconductor manufacturing. As wafer fabrication reaching nano-technology nodes, existing approaches on advanced equipment control and advanced process control (AEC/APC) for variation control of individual processes are increasingly difficult to achieve desired process control due to shrinking process windows. This study aims to propose a novel approach to determine tool affinity to hedge the variation between the photolithography for pattern development and the etching process to effectively reduce the etching bias caused by tool misalignment. In particular, the proposed approach integrates a feed-forward run-to-run (R2R) controller and the proposed mini-max regret tool dispatching rules in light of the tool characteristics of the photolithography and etching processes. To validate the proposed approach, an empirical study was conducted in a leading semiconductor company in Taiwan and the results showed practical viability of the approach.     

A new recurslve method for the analysis of linear time invariant dynamic systems via double-term triangular functions （DTTF） in state space environment

This paper presents a new recursive method for system analysis via double-term triangular functions (DTTF) in state space environment. The proposed method uses orthogonal triangular function sets and proves to be more accurate as compared to single term Walsh series (STWS) method with respect to mean integral square error (MISE). This has been established theoretically and comparison of error with respect to MISE is presented for clarity. A numerical example is treated to establish the proposed method. Relevant curves for the solutions of states of the dynamic system are also presented with plots of percentage error for DTTF-based analysis.