Sidelobe reduction in array-pattern synthesis using geneticalgorithm

A simple and flexible genetic algorithm (GA) for pattern synthesis of antenna array with arbitrary geometric configuration is presented. Unlike conventional GA using binary coding and binary crossover, this approach directly represents the array excitation weighting vectors as complex number chromosomes and uses decimal linear crossover without a crossover site. Compared with conventional GAs, this approach has a few advantages: giving a clearer and simpler representation of the problem, simplifying chromosome construction, and totally avoiding binary encoding and decoding so as to simplify software programming and to reduce CPU time. This method also allows us to impose constraints on phases and magnitudes of complex excitation coefficients for preferable implementation in practice using digital phase shifters and digital attenuators. Successful applications show that the approach can be used as a general tool for pattern synthesis of arbitrary arrays     

基于遗传算法的低频不规则天线阵综合

低频天线工作波长长,辐射性能受载机影响大,且阵列布局受限于安装环境极不规则,从而造成副瓣电平抬高和方向图恶化,传统的阵列综合方法将难以适用,文中采用遗传算法并结合载机影响来优化,以实现所期望的平均副瓣。作为一种优化算法,它能解决一些N维和非线性的优化问题。首先,给出了任意阵列的方向图公式;其次,介绍了遗传算法;最后,给出了应用实例及其优化结果。结果表明,该算法是一种解决多维和非线性问题的行之有效的方法。     

基于实数编码遗传算法的稀布阵列综合

针对有孔径和阵元总数约束的线性阵列,提出了一种基于实数编码遗传算法的稀布阵列综合方法。算法中每条染色体基因主要由阵元间距和激励幅度共同组成,采用双变量组合优化的方式为阵列性能优化提供了更多的自由度。采用十进制实数量化编码的方式,省去了二进制编码过程中的解码运算,使算法程序更为简洁,效率更高。以降低阵列方向图的峰值旁瓣电平为目标函数,运用提出的改进遗传算法针对几种不同的线性阵列进行优化仿真,在同等约束条件下将该算法与其他改进遗传算法进行了优化对比,结果表明该算法表现更为出色。     

平面阵子阵级自适应波束形成方法研究

利用遗传算法(GA)将大型阵列划分为非均匀邻接子阵,以主旁瓣比作为适应度函数,并对遗传操作增加约束条件,得到具有栅瓣抑制能力的子阵结构。为进一步抑制平面阵俯仰和方位上的高旁瓣,对平面阵进行两级子阵划分,使平面阵方向图在俯仰和方位上均具有良好的主旁瓣电平比;为消除非均匀子阵结构各子阵通道噪声功率不同对子阵级自适应波束形成算法的影响,通过对阵列协方差矩阵进行奇异值分解、重构特征子空间,提出了基于特征空间重构的子阵级自适应波束形成方法。仿真结果表明了该方法的可行性与有效性。     

阵列方向图综合的一些方法

介绍了几种常用的阵列方向图综合方法。切比雪夫阵列在指定的副瓣电平下主瓣宽度最窄,在指定的主瓣宽度下副瓣电平最低;相位控制技术通过控制阵列各单元的相位实现波束的指向变化;最后介绍了遗传算法并利用遗传算法优化了8元线阵,将其相对副瓣电平抑制到了-50dB。     

增加副瓣抑制机制的阵列天线波束赋形遗传算法研究

基于遗传算法的激励优化算法是求解阵列天线波束赋形问题时常用的激励求解算法。传统遗传算法在优化阵列天线激励时,对阵元天线方向图矢量叠加获得阵列天线合成方向图后,与目标方向图做相似度判断,经过多次运算获得满足设计要求的激励值。然而算法中通常不关注赋形结果的副瓣抑制,导致阵列天线波束赋形结果副瓣抑制效果不理想。该文提出一种基于一组低副瓣波束线性叠加的波束合成机制,将合成方向图与目标方向图做相似对比,结合遗传算法的优化求解方法,最终获得与目标方向图匹配的合成方向图,且合成方向图具有高副瓣抑制的特性。以一款16阵元 波段微带偶极子线性阵列天线为例,该文提出的具有副瓣抑制机制的遗传算法求得的赋形波束获得了-27.5 的副瓣抑制效果,远远好于传统遗传算法求得的赋形波束-19 的副瓣抑制。     

基于免疫克隆选择算法的天线方向图综合技术研究

方向图综合技术是智能天线中的一项重要技术。由于采用遗传算法存在着易于早熟和局部寻优能力不足等缺点,为此,文中提出一种基于免疫克隆选择算法的阵列方向图综合技术。仿真结果验证了免疫克隆选择算法相对于标准遗传算法来说更容易找到全局最优解,不易陷入局部极值,且收敛速度快,实际应用表明,基于免疫克隆选择算法的方向图综合技术是切实可行的,且具有很好的推广潜力。     

一种综合赋形波束天线阵的组合算法

提出一种新的组合优化方法。先通过遗传算法得到一个初步的优化结果,再用直接搜索算法进行二次优化,这样既突出了遗传算法全局寻优的特点,又避免了它在接近最优解时出现的小幅度随机波动。以低副瓣平方余割波束天线阵的综合为例,在主瓣达到要求的前提下,组合算法得到的天线阵方向图副瓣比直接搜索算法和遗传算法的副瓣低4dB以上。     

Pattern synthesis for uniform linear array using genetic algorithm and artificial neural network

Multidimensional Systems and Signal Processing - In this paper, we propose a new amplitude-only method for pattern synthesis of uniform linear array (ULA) based on genetic algorithm (GA) and...     

基于遗传优化的天线阵元LMS改进算法

最小均方（LMS）算法是自适应阵列天线中得以广泛应用的阵列天线加权算法。提出了一种基于遗传优化的LMS改进算法,该基于遗传优化的最小均方（GA—LMS）算法充分结合了遗传算法的并行处理和全局搜索的优点。实验结果表明,与传统的LMS算法相比,GA—LMS算法具有良好的收敛性能,并可更好地抑制干扰信号,有效改善自适应阵列天...     

波导缝隙阵天线的快速优化设计

本文利用Elliott设计方程考虑波导缝隙阵天线中单元间的耦合效应,提出"电流分布逼近"作为目标函数,利用遗传优化算法对谐振式波导缝隙阵天线进行方向图优化设计.本文设计了一个4元波导缝隙阵,证明了这种方法是有效的,并完成了一个8元缝隙阵的设计实例.数值结果表明,本文方法相比于传统"方向图逼近"优化方法更加快速有效,并且可以应用到大型的波导缝隙阵的设计之中.     

Design of broadband array elements based on neural network and genetic algorithm

Coupled artificial neural network (ANN) and genetic algorithm (GA) models are developed for the design of broadband tapered slot antenna array elements. The ANN is employed to establish the complicated relationships between the key array performance indicator, i.e. active reflection coefficient, and its element parameters. The trained ANN models are combined with the GA to optimise the element parameters for a given operating frequency band without using time-consuming EM simulators. Optimisation results show the developed ANN-GA model can retain the accuracy obtainable from EM simulators and exhibit high computational efficiency.     

基于遗传算法的圆形天线阵波束成形算法

将基于GA(遗传算法)的波束成形算法应用于二维圆形天线阵,研究了算法在解决抑制多个窄角度强干扰问题时的性能;同时提出了一种改进的二进制编码方法,该方法引入了若干参数用以方便地控制解的精度和搜索空间。仿真结果表明,算法可以使得天线阵在主波束对准有用信号的同时,有效地抑制多个强干扰。文中建立的模型适用于卫星通信抗空间恶意干扰问题。     

Sidelobe Reduction of Low‐Profile Array Antenna Using a Genetic Algorithm

A low‐profile phased array antenna with a low sidelobe was designed and fabricated using a genetic algorithm (GA). The subarray distances were optimized by GA with chromosomes of 78 bits, a population of 100, a crossover probability of 0.9, and a mutation probability of 0.005. The array antenna has 24 subarrays in 14 rows, and is designed as a mobile terminal for Ku‐band satellite communication. The sidelobe level was suppressed by 6.5 dB after optimization, compared to the equal spacing between subarrays. The sidelobe level was verified from the far‐field pattern measurement by using the fabricated array antenna with optimized distance.     

大型阵列天线子阵划分及栅瓣抑制方法

利用遗传算法(genetic algorithm, GA)将大型阵列划分为非均匀邻接子阵,以主旁瓣比作为适应度函数,并对遗传操作增加约束条件,得到具有栅瓣抑制能力的子阵结构。提出了基于子阵级的波束扫描方法,在每个扫描分区内无需改变阵元权值,仅通过子阵级数字波束形成即可完成阵列的波束扫描,并分析了不同扫描角对阵列方向图的影响。为了抑制大扫描角带来的高旁瓣,运用自适应原理使子阵级方向图在高旁瓣位置形成凹陷。分析与仿真结果表明,该方法能够进一步提高阵列方向图的主旁瓣比,增加扫描分区的范围。      

基于改进GA-FFT综合含互耦效应的不等间隔阵列赋形方向图

该文提出了一种虚拟的最小均方有源单元方向图展开方法,将不等间隔阵列的有源方向图展开为一个虚拟的均匀间隔阵列的若干单元辐射的叠加。通过该方法,对包含阵元耦合效应的不等间隔阵列方向图,可以使用快速傅里叶变换进行加速计算。并且,该文将这个方法与遗传算法(GA)相结合,得到一种改进的GA-FFT方法,可以应用于解决含阵元互耦的不均匀间隔阵列的赋形波束综合问题。最后,分别对不等间隔的偶极子阵列平顶方向图及微带阵列的余割平方方向图进行了综合,结果表明所提方法的有效性和优势。     

Broad-band fragmented aperture phased array element design using genetic algorithms

In this paper, a synthesis procedure to design thin broad-band fragmented aperture array elements is described. The arrays are assumed to be infinite periodic and the elements consist of a conducting pattern etched on a dielectric backed by a groundplane. A genetic algorithm (GA) is used to design the conducting pattern, relative permittivity, and thickness of the dielectric substrate with respect to array scan and bandwidth performance. The fitness function in the GA is evaluated using a finite-difference time-domain code with periodic boundary conditions. For a substrate thicker than about 0.1 /spl lambda//sub L/ (/spl lambda//sub L/= wavelength at the lowest frequency in the frequency band investigated), it was found that a bandwidth of at least one octave can be obtained for arrays scanned within 45/spl deg/ from broadside.     

Pilot-based joint ML estimation of timing offset,CFO and channel for OFDMA uplink using minimum residue decomposition technique

In this paper, a uniform circular antenna array (UCAA) combining genetic algorithm (GA) or asynchronous particle swarm (APSO) for finding out global maximum of multi-objective function in indoor ultra-wideband (UWB) communication system is proposed. The algorithm is used to synthesize the radiation pattern of the directional UCAA to reduce the bit error rate (BER), to increase received energy and channel capacity in indoor UWB communication system. Using the impulse response of multipath channel, the BER of the synthesized antenna pattern on binary antipodal-pulse amplitude modulation system can be calculated. Based on topography of the antenna and the shooting and bouncing ray/image techniques, the synthesized problem can be reformulated into a multi-objective optimization problem which would be solved by the GA and APSO. Numerical results show that the fitness value and convergence speed by APSO is better than those by GA. The results also show that for multi-objective problem APSO compared to GA can reduce the BER substantially. Moreover, APSO can get better results for both line-of-sight and non line-of-sight cases.     

运用遗传算法综合稀疏阵列

本文运用遗传算法(GA)综合稀疏阵列(单元从规则栅格中稀疏)时,不仅优化单元间距,而且将单元激励也作为优化变量,从而提供了更多的自由度来控制稀疏阵列的性能.其中,单元的幅相加权在数字波束形成天线中可以很容易通过数字方法实现.由于稀疏阵列间隔是栅格的整数倍,因此采用了GA结合快速傅立叶变换的方法加快阵列方向图的评估,提高了优化效率.     

基于遗传算法的智能天线波束形成

为降低智能天线方向图旁瓣电平,加深干扰方向零点深度,提出一种改进的实数编码遗传算法。该算法基于人类的繁殖现象,改进了标准遗传算法的交叉算子,从而克服了标准遗传算法收敛速度慢,易陷入局部最优等问题,提高了优化效率。在仿真实验中,以均匀直线阵为例,用改进的遗传算法对阵元激励的幅度进行优化,形成的方向图获得了更好的结果。