Microwave Foreign Object Detection in a Lossy Medium Using a Planar Array Antenna
The non-contact detection of foreign objects embedded in lossy dielectric media such as soil, vegetation, or ice remains a critical challenge in applications including environmental monitoring and agricultural safety. This communication presents the design and experimental validation of an array ant...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/13/3965 |
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| Summary: | The non-contact detection of foreign objects embedded in lossy dielectric media such as soil, vegetation, or ice remains a critical challenge in applications including environmental monitoring and agricultural safety. This communication presents the design and experimental validation of an array antenna system capable of accurately localizing foreign objects in such lossy mediums. The proposed array antenna is capable of focusing electromagnetic energy at the location of the foreign object, thereby enabling precise positioning. The main idea of the foreign object detection is to set some of the antenna elements as test receiving antennas and measure the scattering parameters between the transmitting antennas and the receiving antennas. The excitation distribution of the transmitting array is optimized by using the method of maximum power transmission efficiency based on the differential scattering parameter matrices with the absence and presence of the foreign object. To validate the proposed design, a 5 × 5 microstrip patch array antenna was fabricated and tested with colza oil as a lossy medium. A copper block immersed in the colza oil served as the foreign object for detection, demonstrating the feasibility of the non-contact detection scheme. Experimental results demonstrate that the radiated field can be effectively focused at the object location, confirming the feasibility and precision of the proposed non-contact detection approach. |
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| ISSN: | 1424-8220 |