幅值比约束下稀布阵的旁瓣抑制混合算法

针对非均匀稀布圆环阵的旁瓣抑制问题提出了一种基于粒子群算法和二阶锥规划算法的混合算法。该混合算法结合两种算法的优势,将粒子群算法作为全局搜索器进行阵元位置的优化,二阶锥规划算法作为局部搜索器进行阵元权值的优化,能够获取较低的峰值旁瓣电平。该算法同时引入相邻阵元最小间距的约束,优化了算法的搜索空间,提高了寻优效率。最后,考虑到阵列天线系统的可实现性,给出了动态幅值比约束下的混合算法。与粒子群算法和参考文献方法的对比实验结果表明:本文算法可进一步降低稀布圆环阵的旁瓣电平,仿真数据验证了算法的有效性和天线系统的可实现性。     

风驱动优化的共享孔径方向图综合

针对共享孔径阵列天线,基于一种新型的全局优化算法——风驱动优化,提出了一种新的共享孔径方向图综合方法。首先,设计两阵列相邻阵元的间距约束条件,将两个子阵波束图的最高旁瓣电平作为优化目标。然后,在约束公式条件下,先后确定子阵1和子阵2阵列单元的初始坐标,通过利用风驱动算法优化两子阵单元坐标位置来降低旁瓣电平,实现不同频率的共享孔径阵列天线设计。最后,通过与粒子群算法和传统SMI算法对比,验证了该算法在共享孔径方向图中的可行性和有效性。     

基于PSO-MUSIC算法的分布式目标DOA估计

提出了一种基于粒子群优化算法（PSO）和多重信号分类（MUSIC）算法的分布式目标波达方向（Direction of Arrival,DOA）估计方法。在空间欠采样情况下,该方法首先利用粒子群优化算法优化阵列阵元间距,得到阵列天线方向图高旁瓣电平最小情况下的阵元间距,阵列阵元间距决定了阵列流形,然后在该阵列流形下构造分布式目标信号模型,最后结合分布式目标导向矢量和MUSIC算法获得空间欠采样情况下分布式目标中心DOA的准确估计。仿真结果表明了该方法的有效性。     

改进CQPSO算法的双频航向信标方向图优化

针对仪表着陆系统中的双频航向信标（localizer,LOC）阵列天线最大旁瓣电平抑制和覆盖性能优化问题,改进了一种混沌量子粒子群（chaos quantum particle swarm optimization,CQPSO）算法,对既定约束的LOC阵列天线方向图进行馈电参数寻优。在分析双频LOC覆盖形成的基础上,剖析了国际民航组织对LOC信号的覆盖要求,获得LOC方向图应满足的约束条件。为提升全局寻优能力和有效避免陷入局部最优,引入混沌思想和加权平均最优位置对CQPSO算法进行改进,使用改进的CQPSO算法对20阵元等间距LOC阵列天线进行约束条件下的馈电参数寻优,并依据所获得的馈电参数仿真分析LOC阵列天线的方向性。仿真实验表明,改进CQPSO算法寻优得到的馈电参数形成的方向图,相比于目前广泛使用的24阵元等间距LOC阵列天线的方向图,在天线数量减少16.67%的情况下,航道信号辐射的最大旁瓣电平降低了3.32 dB,且覆盖性能更好;而相比于目前广泛使用的20阵元不等间距LOC阵列天线的方向图,航道信号辐射的最大旁瓣电平降低了25.55 dB,证明了改进CQPSO算法的有效性。     

一种新混合粒子群算法及其在阵列天线方向图综合中的应用

针对传统粒子群算法(PSO)中存在的易陷入局部最优解和后期收敛速度慢的问题,首次提出一种新混合粒子群算法(NHPSO),采用杂交粒子群算法和固定惯性权重策略,并把简化的二次插值法融入杂交粒子群算法中。实验证明新算法大大提高了收敛速度,改善了解的质量。对阵列天线特殊主瓣形式的波束赋形和旁瓣电平优化结果取得了非常好的效果,计算机仿真证实该新算法应用于此类问题非常有效。     

基于生物地理学算法的稀疏平面阵列优化

天线阵列的相对旁瓣电平和阵元位置为非线性关系。对于非线性关系求最优值问题,用其他优化算法较难求解,而研究采用智能算法求解是一条值得探索的可行路径。提出了一种混合智能算法——改进生物地理学算法,即对生物地理学算法的迁移算子和变异算子进行改进,以提高种群的进化速率,进而优化对称和非对称稀疏平面阵列。仿真结果表明,与以往的算法相比,该算法提高了优化速率,降低阵列的相对旁瓣电平;阵元在阵列孔径内非对称分布比对称分布,所获得的旁瓣电平更低。     

随机错位子阵阵列天线及其优化设计

针对大型的二维平面阵列天线,将随机布阵的概念应用于子阵布阵中,提出基于子阵的随机错位布阵方式,并采用二进制粒子群算法对随机错位子阵的错位方式进行了优化.仿真结果表明:采用随机错位子阵布阵方式,通过粒子群算法优化后,平面阵列天线可以在扫描范围内得到较低的旁瓣,避免了栅瓣的出现.     

圆形稀布阵列天线综合

将智能优化算法应用到圆形阵列天线综合当中,介绍了圆形稀布阵列天线的设计方法,利用入侵杂草算法优化阵列单元的位置,得到旁瓣电平尽量低的方向图。文章介绍的方法不但能够对相邻阵列单元的最小间距、阵列天线孔径尺寸和阵列单元数目进行限制,而且能够降低圆形稀布阵列天线优化过程的复杂程度。     

基于粒子群算法的天线阵方向图优化

雷达阵列天线常涉及方向图综合,而天线阵综合常常是利用优化算法优化单元幅相及间距等参数的过程。粒子群算法具有理论简单、参数少和易于实现等特点,文中基于这一简单易行的优化算法,给出一种阵列天线赋形波束综合方法。通过优化阵列天线中各单元的馈电幅度和相位同时实现主瓣的赋形和副瓣电平的抑制,或通过仅相位加权实现主瓣波束赋形,得到优良的余割平方赋形。通过实例设计验证了粒子群算法优化天线阵方向图的有效性。     

基于遗传算法的球面阵列旁瓣电平优化方法

针对共形球面天线阵列,采用有向天线阵元,在保持阵列孔径不变的条件下,以阵元分布位置作为优化变量,以降低最大相对旁瓣电平为优化目标,运用改进的遗传算法对阵列进行稀疏优化,仿真结果表明:该方法能够降低球形阵列的旁瓣电平,达到了减少阵元个数、降低天线系统成本的目的。     

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.     

任意形状旁瓣波束形成技术研究

在自适应零陷形成的基础上,提出了一种自适应加权算法,用于任意阵型阵列构成具有任意形状旁瓣的波束图,并考虑基元方向性对波束图的影响.给出了实现自适应加权算法的三个步骤,预先设定所需旁瓣形状及旁瓣级,采用循环,最终使旁瓣与预设形状吻合.将该算法用于均匀线阵和抛物线阵,均得到期望的结果,并与道夫-切比雪夫加权作了相应比较.研究表明,基元的方向性对该算法波束形成的影响很小,新算法可以消除基元宽带方向性对波束的影响.     

Phase-only synthesis of minimum peak sidelobe patterns for linearand planar arrays

Minimization of the maximum sidelobe level for a given array geometry by phase-only adjustment of the element excitations is considered. Optimum phases are obtained by using a numerical search procedure to minimize the expression for the pattern sidelobe level with respect to the element phases. Results for both linear and planar arrays of equispaced elements are presented. The data suggests that optimum sidelobe level is a logarithmic function of array size, and optimum patterns have relative efficiencies that are typically somewhat greater than for comparable-amplitude tapered arrays. An analytic synthesis algorithm is presented for use on very large arrays for which the numerical search technique for the minimization of the sidelobe level is computationally impractical. This method produces patterns with characteristics similar to arrays synthesized using the numerical search method, i.e. relatively uniform angular distribution of energy in the sidelobe region, and generally decreasing maximum sidelobe level as the array size is increased     

改进标准粒子群算法的阵列天线综合

针对标准粒子群（Particle Swarm Optimization, PSO）算法应用于非对称副瓣形状方向图综合时,收敛速度慢和容易早熟的缺陷,提出了一种改进标准粒子群算法。该方法借助于修正Taylor综合法先得到连续口径分布,然后通过对其抽样得到粒子群初始化的基本值,对该基本值添加随机值得到PSO优化的初始粒子种群,将该种群用于PSO迭代时,采用“精英”选择思想,即用较好的粒子替代部分较差的粒子,直到满足停止条件。文中给出了运用该方法综合的两个实例,验证了其可行性,并通过多次重复试验,验证了该方法的高效性。     

The Pareto Optimization of Ultrawideband Polyfractal Arrays

The application of global optimization techniques, such as genetic algorithms, to antenna array layouts can provide versatile design methodologies for highly directive, thinned, frequency agile, and shaped-beam antenna systems. However, these methodologies have their limitations when applied to more demanding design scenarios. Global optimizations are not well equipped to handle the large number of parameters used to describe large- antenna arrays. To overcome this difficulty, a new class of arrays was recently introduced called polyfractal arrays that possess properties well suited for the optimization of large- arrays. Polyfractal arrays are uniformly excited with an underlying self-similar geometrical structure that leads to aperiodic element layouts. This paper expands on polyfractal array design methodologies by applying a robust Pareto optimization technique with the goal of reducing the peak sidelobe levels at several frequencies specified over a wide bandwidth. A recursive beamforming algorithm and an autopolyploidy based mutation native to polyfractal geometries are used to dramatically accelerate the genetic algorithm optimization process. This paper also demonstrates that the properties of polyfractal arrays can be exploited to create designs that possess no grating lobes and relatively low sidelobe levels over ultrawide bandwidths. The best example discussed in this paper maintains a dB peak sidelobe level with no grating lobes from a , to more than a minimum spacing between elements, which corresponds to at least a 40:1 bandwidth for the array.     

基于DEA的圆阵旁瓣电平优化方法

由于圆形阵列所具有的特性,使其正得到日益广泛的应用,但是圆阵方向图却具有相对主瓣较高的旁瓣电平。为此,文中针对均匀圆形阵列的天线单元,应用差分进化算法,分别进行唯相位、唯幅度、相位一幅度的方向图综合方法,进行旁瓣电平的优化。仿真结果表明：这些方法可有效地降低圆阵的旁瓣电平,为解决此类问题提供了有益的参考。     

基于副瓣峰值控制的天线阵方向图综合

在干扰入射方向,自适应天线阵方向图会产生零陷,使副瓣电平降低。根据自适应阵列的这一特性,应用一种基于最大输出信噪比准则的改进自适应算法对天线阵进行方向图综合。假定有大量干扰信号施加到方向图副瓣区,通过只对副瓣峰值电平进行控制调整加权值,降低副瓣电平,得到满足副瓣要求的目标方向图,使算法得到简化。可以应用于不等间距直线阵列和矩形平面阵的方向图综合问题。考虑了阵元间的互耦及阵元方向图特性的影响。仿真结果证实了该算法是可行的。     

Interleaved thinned linear arrays

This paper presents three approaches to improving the efficiency of an array aperture by interleaving two arrays in the same aperture area. The interleaved arrays have aperiodic spacings that are integer multiples of a set minimum spacing and are optimized to reduce the maximum sidelobe level. Fully and partially interleaved sum arrays operating at the same frequencies are demonstrated as well as interleaved sum and difference arrays for a monopulse system. A genetic algorithm is used to optimize arrays of isotropic point sources as well as arrays of dipoles modeled using the method of moments. Narrow beamwidths are possible while avoiding high sidelobes. The available aperture area is efficiently used.     

Pattern synthesis for arbitrary arrays using an adaptive arraymethod

This paper presents a new pattern synthesis algorithm for arbitrary arrays based on adaptive array theory. With this algorithm, the designer can efficiently control both mainlobe shaping and sidelobe levels. The element weights optimize a weighted L₂ norm between desired and achieved patterns. The values of the weighting function in the L₂ norm, interpreted as imaginary jammers as in Olen and Compton's (1990) method, are iterated to minimize exceedance of the desired sidelobe levels and minimize the absolute difference between desired and achieved mainlobe patterns. The sidelobe control can be achieved by iteration only on sidelobe peaks. In comparison to Olen and Compton's method, the new algorithm provides a great improvement in mainlobe shaping control. Example simulations, including both nonuniform linear and planar arrays, are shown to illustrate the effectiveness of this algorithm