Radar Imaging using Time Domain Back Projection (TDBP)

This MATLAB project reconstructs Synthetic Aperture Radar (SAR) images using the Time Domain Back Projection (TDBP) algorithm. The data is collected via UAV-based radar, and the project includes signal processing techniques for range resolution, image focusing, despeckling, reflector-based resolution analysis, and trajectory noise impact assessment.

Project Structure

File	Description
dataset_UAV.mat	Dataset containing radar signals, UAV trajectory, reference range axis, etc.
range_resolution.m	Calculates theoretical range resolution using ΔR = c / (2B)
range_resolution_energy.m	Estimates bandwidth from signal energy in frequency domain and computes ΔR
tdbp_reconstruction.m	Main image reconstruction using TDBP + runtime analysis
despeckling.m	Reduces speckle noise using moving average filters (3×3, 5×5, 7×7)
corner_reflectors.m	Analyzes focused SAR patch and computes azimuth & range resolution
trajectory_errors.m	Simulates increasing UAV trajectory noise and visualizes impact on SAR image
mohammadreza_zamani_HW2_10869960.pdf	Report explaining methodology, results, and key visualizations

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Key Concepts

• TDBP Algorithm: High-resolution SAR imaging by integrating radar returns over a 2D grid.
• Range Resolution: Assessed using both known bandwidth and estimated from signal FFT.
• Despeckling: Moving average filters help reduce speckle noise while preserving detail.
• Corner Reflectors: Used to evaluate range and azimuth resolution performance.
• Trajectory Error Simulation: Demonstrates how UAV motion errors distort image quality.

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How to Run

1. Open MATLAB.
2. Ensure all .m files and dataset_UAV.mat are in the same folder or in your MATLAB path.
3. Run each script separately to view results:

run('range_resolution.m')
run('range_resolution_energy.m')
run('tdbp_reconstruction.m')
run('despeckling.m')
run('corner_reflectors.m')
run('trajectory_errors.m')