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Localization of Dielectric Anomalies with Multi-Monostatic S11 Using 2D MUSIC Algorithm with Spatial Smoothing
1Department of Electronic & Information Engineering, Korea Aerospace University, Goyang 10540, Korea.
Sensors (Basel, Switzerland)
|July 27, 2022
Summary
This study shows how antenna S11 data can locate dielectric anomalies using Inverse Synthetic Aperture Radar (ISAR) imaging. This method accurately images hidden objects in various backgrounds, aiding medical diagnostics.
Area of Science:
- Electromagnetics
- Microwave Imaging
- Signal Processing
Background:
- Dielectric anomalies require precise localization methods.
- Near-field antenna measurements present unique challenges for imaging.
- Inverse Synthetic Aperture Radar (ISAR) is a powerful imaging technique.
Purpose of the Study:
- To demonstrate the localization of dielectric anomalies using S11 antenna data.
- To validate a multi-monostatic Inverse Synthetic Aperture Radar (ISAR) imaging framework.
- To adapt the Multiple Signal Classification (MUSIC) algorithm for near-field applications.
Main Methods:
- Utilizing S11 scattering parameters from an antipodal Vivaldi antenna (1-8.5 GHz).
- Applying a 2D MUSIC algorithm with spatial smoothing for data analysis.
- Implementing background and antenna artifact removal by subtracting average S11 values.
Main Results:
- Accurate localization of dielectric anomalies within dielectric backgrounds was achieved.
- The methodology proved effective in both homogeneous and inhomogeneous background media.
- Image noise and resolution were optimized by adjusting data sub-array sizes.
Conclusions:
- Near-field ISAR imaging with S11 data is a viable method for dielectric anomaly localization.
- The developed technique shows promise for applications in medical imaging, such as breast tumor and brain stroke detection.
- The MUSIC algorithm adaptation effectively handles near-field complexities.
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