Sub-Nyquist SAR Based on Pseudo-Random Time-Space Modulation

Area of Science:

• Remote Sensing
• Signal Processing
• Information Theory

Background:

• Sub-Nyquist sampling in Synthetic Aperture Radar (SAR) offers a solution to the high-resolution wide-swath dilemma.
• Current sub-Nyquist SAR methods are limited to reconstructing scenes with low sparsity.
• Information theory provides a framework to understand the limitations of existing sub-Nyquist SAR systems.

Purpose of the Study:

• To overcome the sparsity constraint in sub-Nyquist SAR.
• To enable the reconstruction of complex scenes with high sparsity.
• To broaden the applicability of sub-Nyquist SAR technology.

Main Methods:

• Development of an information channel model for microwave imaging radar.
• Application of noisy-channel coding theorem to explain reconstruction limitations.
• Introduction of pseudo-random space-time modulation for SAR data.

Main Results:

• Pseudo-random space-time modulation increases mutual information between the scene and echo.
• Successful reconstruction of scenes with large sparsity, including oceanic and urban environments.
• Validation of the proposed method through simulations.

Conclusions:

• The proposed sub-Nyquist SAR based on pseudo-random space-time modulation effectively reconstructs scenes with high sparsity.
• This advancement significantly expands the potential applications of sub-Nyquist SAR.
• The method addresses a key limitation in current sub-Nyquist SAR technology.