In this contribution, we consider MUltiple SIgnal Classification (MUSIC)-type algorithm for a non-iterative microwave imaging of small and arbitrary shaped extended anomalies located in a homogeneous media from scattering matrix whose elements are scattering parameters measured at dipole antennas. In order to explain the feasibility of MUSIC in microwave imaging, we investigate mathematical structure of MUSIC by establishing a relationship with an infinite series of Bessel function of integer order and antennas setting. This is based on the representation formula of scattering parameters in the presence of small anomalies and the application of Born approximation. Simulation results using real-data at $f=925$MHz of angular frequency are exhibited to show the feasibility of designed algorithm and to support investigated structure of imaging function.

翻译：本文研究了一种基于MUltiple SIgnal Classification (MUSIC)型算法的非迭代微波成像技术，用于对位于均匀介质中、形状任意的小型扩展异常体进行成像。成像数据来源于偶极天线测得的散射参数所构成的散射矩阵。为阐明MUSIC算法在微波成像中的可行性，我们通过建立与整数阶贝塞尔函数无穷级数及天线配置之间的关系，深入分析了MUSIC的数学结构。该分析基于小异常体存在下的散射参数表示公式以及玻恩近似的应用。文中展示了在角频率$f=925$MHz下使用实测数据的仿真结果，以验证所设计算法的可行性，并支持对所研究成像函数结构的分析。