SBIR Phase II: A Search Engine for Antenna Design

SBIR 第二阶段：天线设计搜索引擎

• 批准号: 1026900
• 负责人: Derek Linden
• 金额: $ 50万
• 依托单位: X5 Systems, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1026900&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Search; Engine

This Small Business Innovation Research (SBIR) Phase II project seeks to develop and launch a software tool that applies advanced AI algorithms to antenna design and optimization. Manual antenna design and optimization methods are time- and labor-intensive, limit complexity, and require significant expertise. Genetic algorithm (GA) optimization has demonstrated success at quickly finding effective antenna design solutions not ordinarily found through engineering intuition. To harness the power of these search algorithms currently, an engineer must be an expert in both GAs and Electromagnetics. In Phase I, feasibility of a highly-automated design approach where useful antennas can be generated without requiring significant guidance was demonstrated: the user simply inputs design requirements (e.g., RF performance, dimensions, etc.), and an automated optimization produces compliant designs. If successful, this technology promises to improve the performance and economics of future antenna applications for commercial and government customers. The world is in the midst of an explosion in the number of new wireless, mobile, and RF systems - all of which rely on one or more antennas. Yet antenna design has changed little in the past two decades, with large up-front costs and slow, inefficient trial-and-error methods. X5 Systems is attempting to bring to market a next generation way to design antennas: one that is faster, better, cheaper. The commercial potential of the proposed software system encompasses application areas of interest to companies in mobile and wireless, RFID, and consumer electronics, as well as government agencies - especially applications that have exacting performance, schedule, and cost requirements.

这个小型企业创新研究(SBIR)第二阶段项目旨在开发和推出一种软件工具，将先进的人工智能算法应用于天线设计和优化。手动天线设计和优化方法耗时耗力，复杂性有限，需要大量专业知识。遗传算法(GA)优化在快速找到有效的天线设计解决方案方面取得了成功，而这些解决方案不是通常通过工程直觉找到的。要利用目前这些搜索算法的强大功能，工程师必须同时是气体和电磁学方面的专家。在第一阶段，展示了一种高度自动化的设计方法的可行性，在这种方法中，可以生成有用的天线，而不需要大量的指导：用户只需输入设计要求(例如，射频性能、尺寸等)，自动优化就会产生符合要求的设计。如果成功，这项技术有望提高商业和政府客户未来天线应用的性能和经济性。世界正处于新的无线、移动和射频系统数量的爆炸式增长之中，所有这些系统都依赖于一个或多个天线。然而，天线设计在过去20年里几乎没有改变，前期成本很高，试验方法缓慢而低效。X5系统公司正试图将下一代天线设计方法推向市场：一种更快、更好、更便宜的方法。拟议软件系统的商业潜力包括移动和无线、RFID和消费电子产品公司以及政府机构感兴趣的应用程序领域，特别是对性能、进度和成本有严格要求的应用程序。