Three-Dimensional Interferometric ISAR Imaging Algorithm Based on Cross Coherence Processing.

Area of Science:

• Radar systems engineering
• Electromagnetics and wave propagation
• Computational imaging

Background:

• Traditional 2D ISAR imaging struggles with interpreting target geometry due to unknown radar-target dynamics.
• 3D imaging using InISAR is crucial for advanced target classification and recognition.

Purpose of the Study:

• To propose a novel 3D target reconstruction algorithm for InISAR systems.
• To jointly estimate effective rotation vectors and scattering center heights.
• To introduce a robust detector for improved imaging accuracy.

Main Methods:

• Utilizes an L-shape InISAR imaging system with Dechirp processing and 2D interferometric ISAR imaging.
• Introduces a cross-channel coherence-based detector (C3D) to mitigate noise and sidelobes.
• Quantitatively analyzes misregistration effects on target reconstruction.

Main Results:

• The proposed algorithm effectively reconstructs 3D targets with multiple scattering points.
• The C3D detector offers lower computational cost and avoids error propagation compared to multichannel CLEAN.
• Demonstrates high efficiency, reliability, and effectiveness in noisy environments.

Conclusions:

• The developed algorithm is suitable for efficient 3D imaging of multi-scattering point targets using InISAR.
• The C3D detector enhances the robustness and applicability of InISAR imaging.
• The method provides a reliable approach for target reconstruction in challenging conditions.