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Area of Science:

  • Remote Sensing
  • Radar Systems
  • Signal Processing

Background:

  • Unmanned aerial vehicle (UAV) borne frequency modulated continuous wave synthetic aperture radars (FMCW SAR) offer cost-effective and flexible imaging capabilities.
  • Small UAVs experience trajectory deviations and range-azimuth coupling due to navigational limitations and air turbulence, degrading image quality.
  • Precise target identification requires high-resolution SAR imagery, which is challenged by motion artifacts in UAV platforms.

Purpose of the Study:

  • To develop and validate a robust signal processing approach for UAV-borne FMCW SAR systems.
  • To mitigate range-azimuth coupling and motion-induced effects for improved image formation.
  • To enhance the precision of target identification through clearer SAR imaging.

Main Methods:

  • Utilized squint minimization technique for coupling reduction and spectrum scaling for intra-pulse motion compensation.
  • Derived a modified range Doppler algorithm incorporating second-order range compression and block-wise range cell migration correction.
  • Implemented raw data-based motion compensation using a Doppler tracker and employed a squinted azimuth dependent phase gradient algorithm.
  • Applied minimum entropy-based autofocusing and azimuth nonlinear chirp scaling for final azimuth compression.

Main Results:

  • The proposed signal processing approach effectively reduces range-azimuth coupling.
  • Intra-pulse motion effects and trajectory deviations are significantly mitigated.
  • High-quality SAR images with enhanced clarity and reduced artifacts were achieved in simulations and real-world experiments.
  • The method demonstrates effectiveness in compensating for azimuth-dependent parameters and inexact deramping.

Conclusions:

  • The developed signal processing strategy is effective for UAV-borne FMCW SAR systems.
  • The approach successfully addresses challenges related to motion compensation and geometric distortions.
  • Validated results confirm the enhanced performance for precise target identification using UAV-borne SAR data.