利用PN码的盲自适应波束形成算法

本文基于卫星导航定位系统接收机的智能天线抗干扰应用背景。研究了利用PN码的盲自适应波束形成算法。首先介绍了LS-DRMTA算法，然后提出了DR-LMS类自适应波束形成算法。仿真结果表明，DR-LMS类算法具有和LS-DRMTA算法；DR-LMS类算法。     

Thinned arrays using genetic algorithms

Large arrays are difficult to thin in order to obtain low sidelobes. Traditional statistical methods of aperiodic array synthesis fall far short of optimum configurations. Traditional optimization methods are not well suited for optimizing a large number of parameters or discrete parameters. This paper presents how to optimally thin an array using genetic algorithms. The genetic algorithm determines which elements are turned off in a periodic array to yield the lowest maximum relative sidelobe level. Simulation results for 200 element linear arrays and 200 element planar arrays are shown. The arrays are thinned to obtain sidelobe levels of less than -20 dB. The linear arrays are also optimized over both scan angle and bandwidth.<>     

Wire-antenna designs using genetic algorithms

There is a large class of electromagnetic radiators designated as wire antennas. As a rule, an inductive process is used to design these antennas. Either an integral equation is formulated or a simulator is used that gives the current distributions on the wires of the antenna, from which the electromagnetic properties of the antenna can then be determined. Once the antenna properties are known, the parameters are optimized, using guides such as intuition, experience, simplified equations, or empirical studies. However, using an electromagnetics simulator in conjunction with a genetic algorithm (GA), it is possible to design an antenna using a completely deductive approach: the desired electromagnetic properties of the antenna are specified, and the wire configuration that most closely produces these results is then synthesized by the algorithm. In this paper, we describe four antennas designed using GAs. The first is a monopole, loaded with a modified folded dipole that was designed to radiate uniform power over the hemisphere at a frequency of 1.6 GHz. The second antenna consists of seven wires, the locations and lengths of which are determined by the GA alone, that radiates waves with right-hand-circular polarization at elevation angles above 10°, also at 1.6 GHz. The last two antennas are modified Yagis. One is designed for a broad frequency band and very low sidelobes at a center frequency of 235 MHz. The other is designed for high gain at a single frequency of 432 MHz. We have built and tested these antennas     

Passive filter design using genetic algorithms

The objective of this paper is to propose a new approach for designing a passive LC filter of the full-bridge rectifier by using genetic algorithms (GAs). The performance of the cost-effective passive LC filter for a constant load depends on the appropriate inductor and capacitor selection. Several design methods are reviewed and a novel design methodology using GAs is proposed in this paper. By using the proposed GA program, designer can quickly find appropriate parameter values to meet the desired circuit performance. Experimental results show that an appropriate combination of the inductor and capacitor selected by the proposed GA program can meet the desired power quality requirement. Different cases of design examples are shown in this paper to verify the performance of the proposed design methodology.     

Post-fabrication clock-timing adjustment using genetic algorithms

To solve the problem of fluctuations in clock timing (also known as "clock skew" problems), we propose an approach for the implementation of post-fabrication clock-timing adjustment utilizing genetic algorithms (GAs). This approach is realized by the combination of dedicated adjustable circuitry and adjustment software, with the values for multiple programmable delay circuits inserted into the clock lines being determined by the adjustment software after fabrication. The proposed approach has three advantages: 1) enhancement in clock frequencies leading to improved operational yields; 2) lower power supply voltages, while maintaining operational yield; and 3) reductions in design times. Two different LSIs have been developed: the first is a programmable delay circuit, developed as an element of the clock-timing adjustment, while the second is a medium-scale circuit, developed to evaluate these advantages in a real chip. Experiments with these two LSIs, as well as a design experiment, have demonstrated these advantages with an enhancement in clock frequency of 25% (max), a reduction in the power-supply voltage of 33%, and a 21% shorter design time.     

Optimization of lithographic masks using genetic algorithms

Due to its cost effectiveness and reliability, wet-chemical etching of silicon is still one of the key technologies for producing bulk-silicon microstructures. In this paper we present an approach for the design of advanced mask sets for anisotropic, wet-chemical etching of silicon. The optimization method of genetic algorithms is used to derive suitable masks for cases where geometrically calculated compensation structures fail. The underlying etch simulation is described as well as the optimization algorithm itself. Design tasks of current research projects are used as examples to illustrate the advantage of using the presented tool. Udo Triltsch was born in Bergisch Gladbach, Germany, in 1976. He received the Dipl.-Ing. degree for Mechanical Engineering from the Technical University of Braunschweig, Germany, in 2002. He is currently working towards his Ph.D. at the Institute for Microtechnology, Braunschweig, Germany. His research interests include: design methodology for MEMS, process simulation and knowledge management. Anurak Phataralaoha was born in Bangkok, Thailand, in 1973. He received the B. Eng. degree for Production Engineering from KMUTT, Thailand in 1995 and Dipl.-Ing. degree for Mechanical Engineering from Technical University of Clausthal, Germany in 2002. He is currently working towards his Ph.D. at the Institute for Microtechnology, Braunschweig, Germany. His research interests include: 3D-tactile sensors, micro machining for silicon, Tribological micro guide. Stephanus Büttgenbach obtained the Diploma and Ph.D. degrees in physics from the University of Bonn, Germany, in 1970 and 1973, respectively. From 1974 to 1985, he was with the Institute of Applied Physics of the University of Bonn, working on atomic and laser spectroscopy. In 1983, he was promoted to Professor of Physics. From 1977 to 1985, he was also a Scientific Associate at CERN in Geneva, Switzerland. In 1985, Dr. Büttgenbach joined the Hahn-Schickard-Society of Applied Research at Stuttgart as Head of the Department of Microtechnology, where he worked on micromechanics, laser microfabrication, and resonant sensors. From 1988 to 1991, he was the Founding Director of the Institute of Micro and Information Technology of the Hahn-Schickard-Society. In 1991, Dr. Büttgenbach became Professor of Microtechnology at the Technical University of Braunschweig. His current research centers on the development and application of micro sensors, micro actuators, and micro systems. Currently, he is Vice President of the Technical University of Braunschweig, where his areas of responsibility are research and technology transfer. Dima Straube was born in Berlin, Germany, in 1977. He received the Dipl.-Ing. degree for Civil Engineering from Technical University of Berlin, Germany, in 2002. He is currently working towards his Ph.D. at the Institute for Engineering Design, Braunschweig. His research interests include: design methodology for MEMS, computer aided design and tolerance management. Hans-Joachim Franke was born in Helmstedt, Germany, on February 14, 1944. He received his diploma in mechanical engineering (Dipl.-Ing.) from the Technical University of Braunschweig, Germany, in 1969. From 1969 to 1976 he was research assistant of Prof. Roth at the Institute for Engineering Design. In 1976 he received his Ph.D. degree in mechanical engineering. From 1976 to 1988 he had diverse executive positions at the KSB-AG in Frankenthal, Germany, a company, which produces pumps and valves. Since 1988 he has been the director of the Institute for Engineering Design of the Technical University of Braunschweig. His research interests are in the areas of design methodology, computer aided design and machine elements.     

Design of Yagi-Uda antennas using genetic algorithms

A method of using genetic algorithms to optimize the element spacing and lengths of Yagi-Uda antennas is presented. A method of moments code, NEC2, performs the task of evaluating each of the antenna designs generated by the genetic algorithm (GA) during the optimization process. To illustrate the capabilities of the method, the length and spacing of several Yagi-Uda antennas are optimized for various performance characteristics. The results are compared to published results from other optimization techniques and to well-designed equally spaced arrays     

Synthesis of antenna arrays using genetic algorithms

In this article, two particular methods for the synthesis of the complex radiation pattern of a linear and a planar array, based on genetic algorithms (GAs), are discussed. First, we present a combination of Schelkunoff's method and GAs for linear arrays with arbitrary radiation patterns; then, we consider the synthesis of planar arrays with rectangular cells. The results show the flexibility of GAs to solve complex problems related to antenna synthesis, subject to many restrictions which are difficult to treat by classical optimization techniques. There is good agreement between the desired and calculated radiation patterns     

Channel assignment in cellular radio using genetic algorithms

The channel assignment problem has become increasingly important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal assignment problem of channels has become increasingly important. Recently Genetic Algorithms (GAs) have been proposed as new computational tools for solving optimization problems. GAs are more attractive than other optimization techniques, such as neural networks or simulated annealing, since GAs are generally good at finding an acceptably good global optimal solution to a problem very quickly. In this paper, a new channel assignment algorithm using GAs is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by GAs. Appropriate GAs operators such as reproduction, crossover and mutation are developed and tested. In this algorithm, the cell frequency is not fixed before the assignment procedures as in the previously reported channel assignment algorithm using neural networks. The average generation numbers and the convergence rates of GAs are shown as a simulation result. When the number of cells in one cluster are increased, the generation numbers are increased and the convergence rates are decreased. On the other hand, with the increased minimal frequency interval, the generation numbers are decreased and the convergence rates are increased. The comparison of the various crossover and mutation techniques in a simulation shows that the combination of two points crossover and selective mutation technique provides better results. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. The goal of this paper is the assignment of the channel frequencies which satisfied these constraints with the lower bound number of channels.     

Optical orthogonal code design using genetic algorithms

A construction technique for optical orthogonal codes (OOCs) using genetic algorithms (GAs) is proposed. The performance of the GA OOCs is compared to that of four existing OOCs. Results show that the GA OOCs have a lower probability of error     

Harmonic optimization of multilevel converters using genetic algorithms

In this letter, a genetic algorithm (GA) optimization technique is applied to determine the switching angles for a cascaded multilevel inverter which eliminates specified higher order harmonics while maintaining the required fundamental voltage. This technique can be applied to multilevel inverters with any number of levels. As an example, in this paper a seven-level inverter is considered, and the optimum switching angles are calculated offline to eliminate the fifth and seventh harmonics. These angles are then used in an experimental setup to validate the results.     

Topological design of local-area networks using genetic algorithms

In this paper, we describe an algorithm for designing local-area networks (LANs) with the objective of minimizing the average network delay. The topology design includes issues such as determination of the number of segments in the network, allocating the users to the different segments, and determining the interconnections and routing among the segments. The determination of the optimal LAN topology is a very complicated combinatorial optimization problem. Therefore, a heuristic algorithm that is based on genetic ideas is used. Numerical examples are provided and the quality of the designs obtained by using the algorithm is compared with lower bounds on the average network delay that are developed     

Design of coherently radiating structures in a linear array geometry using genetic algorithms

The design problem of coherently radiating structures in a linear array geometry is dealt with. The key idea is to accept the unavoidable presence of the mutual coupling between antenna elements but force it to be coherent by including additional passive elements in between the active ones. This design of coherently radiating structures considers the optimization of the spacing between antenna elements by using the well-known method of genetic algorithms. Simulation results for coherently radiating structures with uniform and non-uniform separation are provided. A comparative analysis of the performance of different coherently radiating structures is achieved in order to set new design philosophies in antenna arrays.     

Logical process partitioning in distributed simulation using genetic algorithms

This paper presents a method to partition models in logical processes in the context of distributed simulation. The proposed method uses genetic algorithms to decide on the viability and the partitioning technique most indicated. The input parameters to the genetic algorithm are information about the model (number of elements, communication, arrival and service taxes), and the architecture where the simulation is executed. As result, we have the number of logical processes and their mapping on the distributed environment. Two models were used to evaluate the proposed method.     

Array calibration in the presence of multipath

We present an algorithm for the calibration of sensor arrays in the presence of multipath. The algorithm is based on two sets of calibration data obtained from two angularly separated transmitting points. We show the similarity between the calibration problem and blind identification of SIMO systems and analyze the identifiability of the problem. Simulation results demonstrating the performance of the algorithm are included     

移动通信基站速装铁塔基础方案探讨

探讨移动通信基站速装铁塔基础形式,在传统现浇筏板基础和拼装基础上,创造性的引入后浇混凝土的施工方法,设计开发出了一种新型预制拼装基础,该基础形式既保证了拼装基础的结构安全,又能满足生产、加工、运输、安装的各项条件,具有施工速度快、施工协调难度小、质量易于管控、综合造价低等优势,在交通运输方便、具备良好的施工操作面的地区,新型预制拼装基础可以发挥有效的作用,是具有推广价值的新型单管杆塔基础设计施工方法。     

Novel planar electromagnetic absorber designs using genetic algorithms

A new type of absorber is proposed created by drilling holes in a single layer of lossy material. The new absorber is designed using genetic algorithms to achieve low reflectance over a wide frequency band. Results based on genetic algorithms demonstrate that the new absorber outperforms multilayer absorbers and absorbers embedding frequency selective surfaces between lossy materials. Numerical results are presented for different bandwidths, wave incidence angles, and polarizations.     

近场条件下数字阵列雷达自适应波束形成技术研究

针对近场条件下数字阵列雷达导向矢量幅相非一致性对自适应波束形成（adaptive beamforming,ADBF）算法性能的影响,通过构建近场多通道数字阵列雷达回波信号模型,分析近场多通道信号二维频谱,发现在近场条件下带限干扰信号的频谱会出现非均匀分布,呈现周期性栅格分布特征,造成算法性能下降.本文提出一种具有全新干扰样本选择策略的近场ADBF(near field ADBF, NF-ADBF)算法,通过寻优干扰信号频谱栅格边界,在栅格区间进行多门限样本筛选,离散提取干扰信号样本,构建完备的干扰信号协方差矩阵,提升近场条件下的自适应处理性能.通过在地面搭建仿真试验环境,模拟典型的数字阵列近场工作环境,通过录取试验数据分析并与理论仿真进行对比,验证了近场干扰样本筛选策略和NF-ADBF算法模型的有效性.