Multi-resolution imaging with an optimized number and distribution of sampling points

Area of Science:

• * Imaging Science
• * Electromagnetics
• * Signal Processing

Background:

• * Synthetic Aperture Radar (SAR) tomography is crucial for target reflectivity reconstruction.
• * Previous methods lacked flexibility in determining scanning parameters.

Purpose of the Study:

• * To develop an approach for optimal determination of scanning region dimensions and sampling points in SAR tomography.
• * To enhance target reflectivity reconstruction for multi-view and multi-static SAR imaging.

Main Methods:

• * Recasting reflectivity reconstruction as a finite dimensional algebraic linear inverse problem.
• * Optimizing singular value behavior of the linear operator matrix to determine sampling parameters.
• * Implementing single, multi-resolution, and dynamic multi-resolution imaging capabilities.

Main Results:

• * The proposed method optimally determines scanning region dimension, number, and spatial distribution of sampling points.
• * Achieved enhanced flexibility in target reflectivity reconstruction compared to existing approaches.
• * Validated performance through comprehensive numerical and experimental analysis.

Conclusions:

• * The developed approach offers a flexible and optimal solution for SAR tomography.
• * It significantly improves the accuracy and adaptability of target reflectivity reconstruction.
• * The method is suitable for various SAR imaging scenarios, including single frequency monostatic multi-view and multi-static single-view configurations.