Application and analysis of MUSIC algorithm for anomaly detection in microwave imaging without a switching device

TL;DR

This paper develops a MUSIC-type imaging method for microwave anomaly detection that does not require a switching device, analyzing its mathematical structure and optimizing antenna configurations to improve imaging performance.

Contribution

It introduces a novel MUSIC-type imaging function using scattering data that eliminates the need for a switching device, enhancing practical microwave imaging applications.

Findings

Imaging performance depends heavily on antenna configuration.

Proposed antenna arrangements improve anomaly detection accuracy.

Simulation results validate the theoretical analysis.

Abstract

Although the MUltiple SIgnal Classification (MUSIC) algorithm has demonstrated suitability as a microwave imaging technique for detecting anomalies, there is a fundamental limit that it requires a switching device to be used which permits an antenna to transmit and receive signals simultaneously. In this paper, we design a MUSIC-type imaging function using scattering parameter data to find small anomaly and explore its mathematical structure. Considering the investigated structure, we confirm that the imaging performance is highly dependent on the antenna configurations and suggest an arrangement of antennas to enhance imaging performance. Simulation results with synthetic data are displayed to support theoretical result.