Experimental Validation of a Microwave Imaging Method for Shallow Buried Target Detection by Under-Sampled Data and a...

Area of Science:

• Electromagnetic imaging
• Microwave sensing
• Inverse scattering problems

Background:

• Inspecting electrically large regions in microwave imaging requires extensive data collection, leading to long measurement times and complex configurations.
• Existing methods face challenges with data volume and synchronization requirements for transmitters and receivers.
• A novel algorithm was developed to address these limitations by representing targets as equivalent surface currents.

Purpose of the Study:

• To validate a recently developed microwave imaging algorithm using experimental measurements.
• To demonstrate the algorithm's effectiveness in detecting shallowly buried targets.
• To confirm the feasibility of reducing spatial data and processing frequency data independently.

Main Methods:

• The algorithm models scattering targets as equivalent surface currents on a reference plane.
• Experimental validation involved a sand box with shallowly buried metallic plate targets.
• Data was collected using a fixed horn antenna and a planar measurement aperture, with only frequency synchronization between transmitter and receiver.

Main Results:

• Experimental results confirmed the algorithm's feasibility for detecting shallowly buried targets.
• The method successfully reduced spatial data requirements without aliasing artifacts.
• Independent processing of frequency data was demonstrated, simplifying experimental setup.

Conclusions:

• The validated microwave imaging algorithm offers a practical solution for inspecting large spatial regions.
• The surface current approach effectively detects shallow targets and reduces data acquisition challenges.
• The method's ability to process frequency data independently enhances its applicability and reduces experimental complexity.