Accurate near-field millimeter-wave imaging of concave objects using circular polarizations

Area of Science:

• Electromagnetics and Remote Sensing
• Signal Processing
• Computational Imaging

Background:

• Millimeter-wave (MMW) imaging is crucial for sensing but suffers from artifacts in complex scenarios like concave structures.
• Existing techniques struggle with accurate separation of multi-reflected signals, limiting precise target recognition.
• Concave objects pose significant challenges for current MMW imaging due to signal reflections.

Purpose of the Study:

• To develop an improved MMW imaging technique for accurate reconstruction of concave objects.
• To enhance the precision of MMW imaging by effectively separating signals based on reflection counts.
• To correct image deformation and improve contour accuracy in MMW imaging of complex targets.

Main Methods:

• Utilizing circular polarized measurements to distinguish between odd and even signal reflections.
• Implementing an iterative reconstruction algorithm for automated signal component separation.
• Deriving an observation angle boundary model using stationary phase methods to correct edge deformation.

Main Results:

• Demonstrated accurate reconstruction of concave object contours using the proposed technique.
• Achieved automated separation of signal components based on reflection parity (odd/even).
• Successfully corrected image deformation, improving edge representation in MMW images.

Conclusions:

• The proposed circular polarization-based MMW imaging technique significantly improves accuracy for concave objects.
• The iterative reconstruction and angle boundary model offer enhanced automation and precision.
• This method advances MMW imaging capabilities for applications requiring detailed object recognition.