MATLAB Code Implementation for SAR Point Target Imaging

This article presents a MATLAB implementation of SAR point target imaging using the Range-Doppler (RD) algorithm for multi-point target processing. First, we need to understand the concept of SAR point target imaging - a synthetic aperture radar (SAR) methodology focused on accurate detection and positioning of targets in SAR imagery. Typically, these targets represent small ground features such as vehicles, buildings, or other objects. The RD algorithm, a commonly used approach in SAR image processing, leverages phase information from SAR signals to enhance image quality. This algorithm combines signals from multiple receiving channels to improve both resolution and signal-to-noise ratio, making it particularly suitable for multi-point target imaging applications. The MATLAB implementation includes key functions for signal processing, including range compression, azimuth compression, and phase compensation. The code handles radar signals from different directions through proper antenna pattern modeling and Doppler parameter estimation. Core algorithmic components involve Fourier transform operations for range-cell migration correction and matched filtering techniques for optimal focus. The program structure consists of three main modules: data preprocessing (including calibration and formatting), RD algorithm processing (with submodules for range and azimuth processing), and image formation (including geocoding and visualization). Implementation details include windowing functions for sidelobe reduction and interpolation methods for precise coordinate transformation. In summary, this SAR point target imaging MATLAB program enables more accurate target detection and positioning, thereby significantly improving the quality and reliability of SAR imaging systems. The modular code design allows for easy customization and integration with additional SAR processing techniques.