基于未知源域重构的无相位近场测量技术

天线的远场对于研究天线辐射特性具有重大意义，由于远场的直接测量有着诸多限制，近场测量技术计算远场因其简洁准确的特点得到广泛应用. 然而，传统的近场测量技术要求获取近场区的幅度和相位分布才能发挥作用，随着天线频率的升高，人们想要在近场区获取准确的相位信息变得十分困难. 为了解决该技术难题，文中提出一种无相位近场测量技术. 利用一个封闭面上的幅度信息重建或猜测出包围待测天线的球面切向电场分布，并采用遗传算法进行全局优化，其最初为四组随机数据，经过数次优化后将逐渐接近准确结果. 仿真结果表明，本文方法能够在忽略相位信号的前提下，计算出准确的远场辐射特性.

The technique for near-field measurement based on reconstructing an unknown source domain using amplitude-only data

The far-field of an antenna under test (AUT) is very important for studying the radiation characteristics of AUT, and the near-field measurement techniques are widely applied because the techniques can avoid direct measurement of far-field. However, the conventional near-field measurement technology requires the acquisition of the amplitude and phase distribution in near-field. Nevertheless, owing to various factors, it is becoming increasingly difficult to obtain the accurate phase information in near-field with the rise in frequency, especially at millimeter wave and sub-millimeter frequency ranges. To solve this problem, we propose a method of near-field measurement using amplitude-only data to reconstruct or guess the spherical tangential electric field distribution enclosing the AUT from the amplitude-only data over a closely complete surface. The electric field exploiting genetic algorithm (GA) for global optimization is originally derived from four random initial estimation of field distributions and will gradually approximate to the exact value during iterations. The simulation results show that combining the phase-free near-field measurement technology and genetic algorithm optimization can calculate accurate far-field radiation characteristics under the premise of ignoring the phase signal.