Explore MATLAB source code curated for "合成孔径雷达" with clean implementations, documentation, and examples.
The Extended CS Algorithm for SAR provides more practical and efficient radar imaging compared to conventional CS algorithms, featuring enhanced noise robustness and computational efficiency.
This resource covers three key SAR imaging algorithms implemented in MATLAB, designed specifically for beginners to learn practical implementation techniques and understand radar signal processing fundamentals.
Range Doppler algorithm implementation program for Synthetic Aperture Radar imaging with practical applications and code implementation details
Implementation of CS imaging algorithms for RADARSAT raw data processing and Synthetic Aperture Radar (SAR) technology with code-level explanations
Comprehensive MATLAB implementation for Synthetic Aperture Radar (SAR) image processing with detailed code explanations, algorithm descriptions, and practical applications
Doppler center estimation for measured SAR echo data utilizing the energy balancing method with implementation insights and algorithm analysis
Synthetic Aperture Radar Point Target Simulation Implementation Reference with Algorithm Explanations
A comprehensive DPCA (Displaced Phase Center Antenna) processing program for Synthetic Aperture Radar systems, featuring advanced clutter suppression algorithms and motion compensation techniques for improved radar data analysis
MATLAB code and technical explanation for linear frequency modulated (LFM) signal pulse compression - a fundamental signal processing technique widely used in Synthetic Aperture Radar (SAR) systems
Phase Gradient Autofocus algorithm for Synthetic Aperture Radar (SAR) motion compensation... highly effective... implemented in four distinct stages involving data preprocessing, autofocus processing, motion compensation, and postprocessing.