Spatial-Variant SAR Range Cell Migration Correction Using Subaperture Strategy.

Area of Science:

• Remote Sensing
• Signal Processing
• Electromagnetics

Background:

• Synthetic Aperture Radar (SAR) imaging faces challenges with highly squinted data due to range-azimuth coupling.
• Existing Range Walk Correction (RWC) methods do not fully address residual, spatially variant Range Cell Migration (RCM).

Purpose of the Study:

• To propose and validate a precise spatial-variant Range Cell Migration Correction (RCMC) method for highly squinted SAR data.
• To improve the focusing of SAR images by accurately compensating for complex RCM effects.

Main Methods:

• A two-stage RCMC approach is presented, starting with coarse correction of the dominant range-variant RCM.
• Azimuth subaperture (SA) processing is employed in the second stage, utilizing a modified Spectrum Analysis (SPECAN) algorithm.
• An SA-image-domain RCMC is developed using interp correction, linking Doppler frequency to residual RCM.

Main Results:

• The proposed method precisely compensates for space-variant RCM, crucial for highly squinted SAR data.
• Simulated and real measured data experiments demonstrate the effectiveness of the subaperture processing approach.
• The algorithm shows improved practicality for real-time SAR processing systems.

Conclusions:

• The developed subaperture-based RCMC method effectively overcomes the limitations of traditional RWC and RCMC techniques for highly squinted SAR.
• This approach enhances SAR image quality and is suitable for real-time applications.