基于混沌粒子群算法的宽零陷方向图综合方法

自适应阵列天线常需要采用宽零陷技术,以增强阵列天线抗干扰的稳健性。为此,提出了一种基于混沌粒子群算法（CPSO）的阵列天线宽零陷方向图综合方法。该算法首先采用混沌序列初始化粒子位置,以增强搜索多样性,并在对部分非优胜粒子的位置更新时引入混沌扰动项,在每次迭代中对全局最优位置进行变尺度混沌优化,提高了全局和局部搜索能力,加快了收敛速度。仿真结果验证了混沌粒子群算法在阵列天线宽零陷方向图综合时的收敛速度和精度方面均优于标准粒子群算法。     

三次型权值粒子群算法用于共形阵列宽零陷综合

本文提出了一种改进的粒子群算法,并用于圆柱阵宽零陷综合的幅度对称优化。采用周期性三次型惯性权值变化策略,同时对适应度值进行实时监测判定并对粒子重新赋值,明显改善了原有算法的收敛速度,有效避免了算法收敛于局部最优。仿真实验表明,对给定条件下的有向圆柱阵列,能够实现含多个宽零陷的方向图,且迭代次数明显降低,证明了该算法的正确性和有效性。      

粒子群优化算法用于阵列天线方向图综合设计

粒子群优化算法是基于一群粒子的智能运动而产生的一类随机进化算法,其优点是算法非常利于理解和应用.本文介绍了粒子群算法的原理和流程,研究了如何将这种方法运用于天线阵的方向图综合上,给出了PSO算法在综合阵列方向图的应用实例,表明粒子群算法在天线阵列综合中具有广泛的应用前景.     

基于粒子群优化算法的阵列天线方向图综合

粒子群优化算法（PSO）是一种基于群智能的随机优化算法,其理论简单,参数少,易于实现,可用于解决大量非线性、不可微和多峰值的复杂问题。本文介绍了粒子群算法的基本原理和基本流程,研究了如何将这种方法应用于阵列天线的方向图综合上,给出了PSO 算法在阵列天线方向图综合的应用实例,结果表明粒子群算法在阵列天线方向图综合上有很好的应用前景。     

中心粒子群优化算法

在线性递减权重粒子群优化算法(LDWPSO)中提到了中心粒子这一概念,进而提出了中心粒子群优化算法(中心PSO)。在线性递减权重粒子群优化算法中,中心粒子不像其它一般的粒子,中心粒子没有明确的速度,并且被始终置于粒子群的中心。此外,在神经网络训练算法中比较中心粒子群优化算法和线性递减权重粒子群优化算法,结果表明:中心粒子群优化算法的性能优于线性递减权重粒子群优化算法。     

基于EIRP最优的智能天线阵赋型算法研究

在实际天线阵列中,由于互耦的影响会使得单天线阵元辐射方向图畸变,导致传统的波束赋形算法性能恶化甚至失效。针对这个问题,文中提出了基于等效全向功率约束条件的粒子群算法,避免了传统的波束赋形算法的失效,提升了系统的等效全向功率。同时,为了减弱干扰方向的影响,文中进一步提出了零陷生成方案。仿真结果显示本文提出的算法不仅能够提升波束的等效全向功率,而且可以有效地生成干扰方向的零陷。     

无线电设备、电信设备

TN802 2007011063粒子群优化算法用于阵列天线方向图综合设计/焦永昌,杨科,陈胜兵,张福顺(西安电子科技大学天线与微波技术国家重点实验室)//电波科学学报.―2006,21(1).―16～20,25.粒子群优化算法是基于一群粒子的智能运动而产生的一类随机进化算法,其优点是算法非常利于理解和应用。该文介绍了粒子群算法的原理和流程,研究了如何将该方法运用于天线阵的方向图综合上,给出了PSO算法在综合阵列方向图的应用实例,表明粒子群算法在天线阵列综合中具有广泛的应用前景。图6表3参13     

量子粒子群多目标优化算法及其在云计算调度优化中的应用研究

粒子群算法是一种新的模仿鸟类群体行为的智能优化算法,现已成为进化算法的一个新的重要分支。基本粒子群算法和改进粒子群算法的原理对科技发展有相当重要的作用。本文主要分析了子群算法在函数优化、图像压缩和基因聚类中的应用,得出了粒子群算法的应用综述和相关程序代码。     

基于差分粒子群优化的MIMO雷达阵列综合

提出一种基于差分粒子群优化算法(Differential Particle Swarm Optimization, DPSO)的MIMO 雷达方向图综合方法,通过发射、接收阵元位置和激励幅度的联合优化,可实现MIMO 雷达方向图旁瓣电平与零陷深度的联合控制。在粒子位置和速度更新机制的基础上,引入差分进化(Differential Evolution, DE)思想而设计的交叉、变异和位置扰动策略以保持种群在迭代后期的搜索多样性,从而改善算法的全局寻优性能。数值实验结果验证了所提方法的有效性以及相对其他算法的性能优势。     

一种新的粒子群优化的图像匹配算法

针对粒子群算法在图像匹配中易陷入局部最优、搜索速度慢以及匹配精度不高的问题,提出一种新的粒子群优化的图像匹配算法。首先,以改进的非线性惯性权重对粒子群算法进行优化,以此来平衡粒子在全局和局部的搜索能力;其次,提出添加动态扰动项对速度进行扰动,避免粒子在算法后期速度停滞为零而陷入局部最优。仿真结果表明,该算法提高了粒子的全局搜索能力和收敛精度,有效防止早熟现象,与基于标准的PSO图像匹配算法相比,所提算法具有收敛速度快、鲁棒性好以及匹配精度高的特点。     

MIMO系统中改进的二进制粒子群天线选择算法

在多输入多输出系统中,发射端和接收端的多天线配置提高了信道容量和传输可靠性,而天线选择技术能在保持系统优点的同时有效地降低运算复杂度以及硬件成本。为了能在时变的信道条件下快速地选择出一组最优的天线子集,提出了一种基于二进制粒子群算法的改进的天线选择算法。推导出了二进制粒子群联合收发端天线选择的信道容量公式,并将其作为粒子群算法的适应度函数,使天线选择问题转换成二进制编码串的组合优化问题。通过改进模糊函数提高粒子群算法的收敛性,让二进制粒子群尽可能地收敛于全局最优位置。仿真结果表明,改进的算法能在降低运算复杂度的同时提高收敛性,且系统信道容量趋近于最优算法。     

粒子群阵列天线方向图适应值函数研究

在粒子群算法优化阵列天线方向图时,适应值函数的选取对算法收敛和优化效率都有着至关重要的影响。针对复杂多指标方向图优化容易早熟收敛,提出了一种分步的适应值函数策略,通过分阶段提高优化指标,可以更好地促进算法收敛和提升优化效率。仿真结果表明:将此适应值策略应用于天线方向图综合中,在不改变算法本身的同时,可以在多零点和低旁瓣约束情况下取得更好的优化效果。     

Comparison of different antenna arrays for the BER reduction in indoor wireless communication

In this paper, we use the ultra wideband antenna array combined with particle swarm optimization (PSO) to minimize the BER for indoor communication systems. Three types of antenna arrays, namely the circular shape, L shape, and Y shape arrays, are used in the transmitter and their corresponding BER on several paths in the indoor environment are calculated. On the basis of the topography of the antenna array and the BER formula, the array pattern synthesis problem can be reformulated into an optimization problem and solved by the PSO. The novelties of our approach is not only choosing BER as the object function instead of the sidelobe level of the antenna pattern, but also considering the antenna feed length effect of each array element. The particle swarm optimization algorithm is employed to optimize the excitation voltages and feed lengths for these antenna arrays to reduce the BER. The strong point of the PSO is that it can find the solution even if the performance index cannot be formulated by simple equations. By the obtained antenna patterns, we can know the route with the lowest BER; meanwhile, transmission power using this route can be reduced. Numerical results show that the synthesized antenna array pattern is effective in focusing maximum gain to the line‐of‐sight path for these antenna arrays. The synthesized array pattern also can mitigate severe multipath fading in complex propagation environments. As a result, the BER can be reduced substantially in indoor ultra wideband communication systems. The investigated results can help communication engineers improve their planning and design of indoor wireless communication.Copyright © 2011 John Wiley & Sons, Ltd.     

基于改进型粒子群算法的阵列天线综合

粒子群优化(PSO)算法是一种通过粒子之间的合作与竞争来实现复杂多维空间的最优区域搜索的优化算法。本文中改进型PSO算法(NPSO),通过增加积分控制项改善了PSO算法全局搜索能力,并将该方法应用于多元环形阵列天线方向图的综合,实现了阵列方向图与预先给定的目标方向图的高度逼近。最后通过数值实例说明这种NPSO方法的有效性。     

A modified PSO technique using heterogeneous boundary conditions for broadband compact microstrip antenna designing

A modified particle swarm optimization (PSO) variant is implemented on a conventionally optimized broadband antenna. Proposed algorithm uses heterogeneous boundary conditions to particles that fly out of the search space. Search space boundary conditions were chosen depending on which bound was violated. The algorithm is executed using MATLAB for the PSO computations and IE3D. Microstrip antennae inherently suffer from low bandwidth. Thus, a broadband patch antenna is optimized to improve the antenna return loss bandwidth in order to validate the proposed algorithm. For the patch antenna, a significant 12 % bandwidth improvement and 20.84 % size reduction was achieved. It was fabricated and satisfactory conformity was found with simulated results.     

基于改进粒子群算法的天线方向图综合技术

针对基本粒子群算法的早熟收敛、易收敛于局部极值的特点，提出一种改进的粒子群优化算法，采用对全局最佳微扰和惯性权重跳变阈值的设置改善了算法的优化速度和收敛精度。经过对一系列测试函数的计算，证明该方法具有良好的优化效果。最后，给出了该方法应用于阵列天线方向图综合中的模型和仿真实例。     

Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs

This paper presents a novel evolutionary optimization methodology for multiband and wide-band patch antenna designs. The particle swarm optimization (PSO) and the finite-difference time-domain (FDTD) are combined to achieve the optimum antenna satisfying a certain design criterion. The antenna geometric parameters are extracted to be optimized by PSO, and a fitness function is evaluated by FDTD simulations to represent the performance of each candidate design. The optimization process is implemented on parallel clusters to reduce the computational time introduced by full-wave analysis. Two examples are investigated in the paper: first, the design of rectangular patch antennas is presented as a test of the parallel PSO/FDTD algorithm. The optimizer is then applied to design E-shaped patch antennas. It is observed that by using different fitness functions, both dual-frequency and wide-band antennas with desired performance are obtained by the optimization. The optimized E-shaped patch antennas are analyzed, fabricated, and measured to validate the robustness of the algorithm. The measured less than - 18 dB return loss (for dual-frequency antenna) and 30.5% bandwidth (for wide-band antenna) exhibit the prospect of the parallel PSO/FDTD algorithm in practical patch antenna designs.     

Design of Linear Phased Array for Interference Suppression Using Array Polynomial Method and Particle Swarm Optimization

In this work, a linear phased array pattern design with null steering is achieved using the array polynomial technique and the Particle Swarm Optimization (PSO) algorithm. The null steering for interference suppression is obtained by controlling some of the roots on the Schelkunoff’s unit circle while keeping the roots responsible for the main beam unchanged. The rest of the roots are controlled to minimize the Side Lobe Level (SLL) of the array pattern using the PSO algorithm. It has been demonstrated that this technique achieved more than 50% reduction in the parameters needed to be optimized compared with the conventional complex coefficients optimization techniques. Consequently, the fitness function is only responsible for the SLL as the prescribed controlled nulls and the mainbeam characteristics are solved analytically. The simulated results show the effectiveness of the proposed technique.