Radar Imaging using Time Domain Back Projection (TDBP)

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')