It has been demonstrated that the MUltiple SIgnal Classification (MUSIC) algorithm is fast, stable, and effective for localizing small anomalies in microwave imaging. For the successful application of MUSIC, exact values of permittivity, conductivity, and permeability of the background must be known. If one of these values is unknown, it will fail to identify the location of an anomaly. However, to the best of our knowledge, no explanation of this failure has been provided yet. In this paper, we consider the application of MUSIC to the localization of a small anomaly from scattering parameter data when complete information of the background is not available. Thanks to the framework of the integral equation formulation for the scattering parameter data, an analytical expression of the MUSIC-type imaging function in terms of the infinite series of Bessel functions of integer order is derived. Based on the theoretical result, we confirm that the identification of a small anomaly is significantly affected by the applied values of permittivity and conductivity. However, fortunately, it is possible to recognize the anomaly if the applied value of conductivity is small. Simulation results with synthetic data are reported to demonstrate the theoretical result.

中文翻译：

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MUSIC型成像在无背景信息异常检测中的应用


事实证明，多重信号分类 (MUSIC) 算法快速、稳定且有效地定位微波成像中的小异常。为了成功应用 MUSIC，必须知道背景的介电常数、电导率和磁导率的精确值。如果这些值之一未知，则无法识别异常位置。然而，据我们所知，尚未对此次失败提供任何解释。在本文中，我们考虑在背景的完整信息不可用时，应用音乐来定位散射参数数据中的小异常。借助散射参数数据的积分方程公式框架，推导了整数阶贝塞尔函数无穷级数的MUSIC型成像函数的解析表达式。根据理论结果，我们确认小异常的识别受到介电常数和电导率应用值的显着影响。然而，幸运的是，如果应用的电导率值较小，则可以识别异常。报告使用合成数据的模拟结果来证明理论结果。