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Radar Imaging using Time Domain Back Projection (TDBP)

Despeckled Image

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

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.

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')