A Data-Driven Approach to SAR Data-Focusing

Area of Science:

• Remote Sensing
• Signal Processing
• Radar Imaging

Background:

• Synthetic Aperture RADAR (SAR) is a powerful imaging technique requiring precise sensor data for focusing.
• Existing model-based SAR algorithms necessitate detailed mission parameters and ancillary data, complicating low-cost sensor development.

Purpose of the Study:

• To develop a SAR data-focusing algorithm that does not require prior knowledge of mission parameters or ancillary data.
• To demonstrate the extraction of essential sensor reference functions directly from raw SAR data using a strong point scatterer.

Main Methods:

• Exploiting the coherent illumination of SAR data.
• Utilizing Singular Value Decomposition (SVD) to analyze raw data matrix redundancy.
• Employing phase unwrapping and polynomial fitting to reconstruct range and azimuth reference functions.

Main Results:

• Successfully generated focused SAR images from both synthetic and real raw data without mission parameters.
• Demonstrated the ability to extract azimuth beam patterns and other sensor parameters as a byproduct.
• Achieved focused images and pulse responses comparable to traditional Range-Doppler (RD) processing.

Conclusions:

• The proposed SAR processing technique effectively focuses images and extracts sensor information without relying on ancillary data.
• This method offers a viable solution for developing simplified, low-cost SAR systems for diverse applications.
• The algorithm shows good adherence to standard processing techniques, validating its performance.